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what are different types of data presentation

Data Presentation - Types & Its Importance

What is data presentation.

Data Analysis and Data Presentation have a practical implementation in every possible field. It can range from academic studies, commercial, industrial and marketing activities to professional practices.

In its raw form, data can be extremely complicated to decipher and in order to extract meaningful insights from the data, data analysis is an important step towards breaking down data into understandable charts or graphs.

Data analysis tools used for analyzing the raw data which must be processed further to support N number of applications.

Therefore, the processes or analyzing data usually helps in the interpretation of raw data and extract the useful content out of it. The transformed raw data assists in obtaining useful information.

Once the required information is obtained from the data, the next step would be to present the data in a graphical presentation.

The presentation is the key to success. Once the information is obtained the user transforms the data into a pictorial Presentation so as to be able to acquire a better response and outcome.

Methods of Data Presentation in Statistics

1. pictorial presentation.

pictorial-presentation

It is the simplest form of data Presentation often used in schools or universities to provide a clearer picture to students, who are better able to capture the concepts effectively through a pictorial Presentation of simple data.

2. Column chart

what are different types of data presentation

It is a simplified version of the pictorial Presentation which involves the management of a larger amount of data being shared during the presentations and providing suitable clarity to the insights of the data.

3. Pie Charts

pie-chart

Pie charts provide a very descriptive & a 2D depiction of the data pertaining to comparisons or resemblance of data in two separate fields.

4. Bar charts

Bar-Charts

A bar chart that shows the accumulation of data with cuboid bars with different dimensions & lengths which are directly proportionate to the values they represent. The bars can be placed either vertically or horizontally depending on the data being represented.

5. Histograms

what are different types of data presentation

It is a perfect Presentation of the spread of numerical data. The main differentiation that separates data graphs and histograms are the gaps in the data graphs.

6. Box plots

box-plot

Box plot or Box-plot is a way of representing groups of numerical data through quartiles. Data Presentation is easier with this style of graph dealing with the extraction of data to the minutes of difference.

what are different types of data presentation

Map Data graphs help you with data Presentation over an area to display the areas of concern. Map graphs are useful to make an exact depiction of data over a vast case scenario.

All these visual presentations share a common goal of creating meaningful insights and a platform to understand and manage the data in relation to the growth and expansion of one’s in-depth understanding of data & details to plan or execute future decisions or actions.

Importance of Data Presentation

Data Presentation could be both can be a deal maker or deal breaker based on the delivery of the content in the context of visual depiction.

Data Presentation tools are powerful communication tools that can simplify the data by making it easily understandable & readable at the same time while attracting & keeping the interest of its readers and effectively showcase large amounts of complex data in a simplified manner.

If the user can create an insightful presentation of the data in hand with the same sets of facts and figures, then the results promise to be impressive.

There have been situations where the user has had a great amount of data and vision for expansion but the presentation drowned his/her vision.

To impress the higher management and top brass of a firm, effective presentation of data is needed.

Data Presentation helps the clients or the audience to not spend time grasping the concept and the future alternatives of the business and to convince them to invest in the company & turn it profitable both for the investors & the company.

Although data presentation has a lot to offer, the following are some of the major reason behind the essence of an effective presentation:-

  • Many consumers or higher authorities are interested in the interpretation of data, not the raw data itself. Therefore, after the analysis of the data, users should represent the data with a visual aspect for better understanding and knowledge.
  • The user should not overwhelm the audience with a number of slides of the presentation and inject an ample amount of texts as pictures that will speak for themselves.
  • Data presentation often happens in a nutshell with each department showcasing their achievements towards company growth through a graph or a histogram.
  • Providing a brief description would help the user to attain attention in a small amount of time while informing the audience about the context of the presentation
  • The inclusion of pictures, charts, graphs and tables in the presentation help for better understanding the potential outcomes.
  • An effective presentation would allow the organization to determine the difference with the fellow organization and acknowledge its flaws. Comparison of data would assist them in decision making.

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10 Methods of Data Presentation with 5 Great Tips to Practice, Best in 2024

10 Methods of Data Presentation with 5 Great Tips to Practice, Best in 2024

Leah Nguyen • 27 Oct 2023 • 10 min read

Finding ways to present information effectively? You can end deathly boring and ineffective data presentation right now with our 10 methods of data presentation . Check out the examples from each technique!

Have you ever presented a data report to your boss/coworkers/teachers thinking it was super dope like you’re some cyber hacker living in the Matrix, but all they saw was a pile of static numbers that seemed pointless and didn’t make sense to them?

Understanding digits is rigid . Making people from non-analytical backgrounds understand those digits is even more challenging.

How can you clear up those confusing numbers in the types of presentation that have the flawless clarity of a diamond? So, let’s check out best way to present data. 💎

Table of Contents

  • What are Methods of Data Presentations?
  • #1 – Tabular

#2 – Text

#3 – pie chart, #4 – bar chart, #5 – histogram, #6 – line graph, #7 – pictogram graph, #8 – radar chart, #9 – heat map, #10 – scatter plot.

  • 5 Mistakes to Avoid
  • Best Method of Data Presentation

Frequently Asked Questions

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What are Methods of Data Presentation?

The term ’data presentation’ relates to the way you present data in a way that makes even the most clueless person in the room understand. 

Some say it’s witchcraft (you’re manipulating the numbers in some ways), but we’ll just say it’s the power of turning dry, hard numbers or digits into a visual showcase that is easy for people to digest.

Presenting data correctly can help your audience understand complicated processes, identify trends, and instantly pinpoint whatever is going on without exhausting their brains.

Good data presentation helps…

  • Make informed decisions and arrive at positive outcomes . If you see the sales of your product steadily increase throughout the years, it’s best to keep milking it or start turning it into a bunch of spin-offs (shoutout to Star Wars👀).
  • Reduce the time spent processing data . Humans can digest information graphically 60,000 times faster than in the form of text. Grant them the power of skimming through a decade of data in minutes with some extra spicy graphs and charts.
  • Communicate the results clearly . Data does not lie. They’re based on factual evidence and therefore if anyone keeps whining that you might be wrong, slap them with some hard data to keep their mouths shut.
  • Add to or expand the current research . You can see what areas need improvement, as well as what details often go unnoticed while surfing through those little lines, dots or icons that appear on the data board.

Methods of Data Presentation and Examples

Imagine you have a delicious pepperoni, extra-cheese pizza. You can decide to cut it into the classic 8 triangle slices, the party style 12 square slices, or get creative and abstract on those slices. 

There are various ways for cutting a pizza and you get the same variety with how you present your data. In this section, we will bring you the 10 ways to slice a pizza – we mean to present your data – that will make your company’s most important asset as clear as day. Let’s dive into 10 ways to present data efficiently.

#1 – Tabular 

Among various types of data presentation, tabular is the most fundamental method, with data presented in rows and columns. Excel or Google Sheets would qualify for the job. Nothing fancy.

a table displaying the changes in revenue between the year 2017 and 2018 in the East, West, North, and South region

This is an example of a tabular presentation of data on Google Sheets. Each row and column has an attribute (year, region, revenue, etc.), and you can do a custom format to see the change in revenue throughout the year.

When presenting data as text, all you do is write your findings down in paragraphs and bullet points, and that’s it. A piece of cake to you, a tough nut to crack for whoever has to go through all of the reading to get to the point.

  • 65% of email users worldwide access their email via a mobile device.
  • Emails that are optimised for mobile generate 15% higher click-through rates.
  • 56% of brands using emojis in their email subject lines had a higher open rate.

(Source: CustomerThermometer )

All the above quotes present statistical information in textual form. Since not many people like going through a wall of texts, you’ll have to figure out another route when deciding to use this method, such as breaking the data down into short, clear statements, or even as catchy puns if you’ve got the time to think of them.

A pie chart (or a ‘donut chart’ if you stick a hole in the middle of it) is a circle divided into slices that show the relative sizes of data within a whole. If you’re using it to show percentages, make sure all the slices add up to 100%.

Methods of data presentation

The pie chart is a familiar face at every party and is usually recognised by most people. However, one setback of using this method is our eyes sometimes can’t identify the differences in slices of a circle, and it’s nearly impossible to compare similar slices from two different pie charts, making them the villains in the eyes of data analysts.

a half-eaten pie chart

Bonus example: A literal ‘pie’ chart! 🥧

The bar chart is a chart that presents a bunch of items from the same category, usually in the form of rectangular bars that are placed at an equal distance from each other. Their heights or lengths depict the values they represent.

They can be as simple as this:

a simple bar chart example

Or more complex and detailed like this example of presentation of data. Contributing to an effective statistic presentation, this one is a grouped bar chart that not only allows you to compare categories but also the groups within them as well.

an example of a grouped bar chart

Similar in appearance to the bar chart but the rectangular bars in histograms don’t often have the gap like their counterparts.

Instead of measuring categories like weather preferences or favourite films as a bar chart does, a histogram only measures things that can be put into numbers.

an example of a histogram chart showing the distribution of students' score for the IQ test

Teachers can use presentation graphs like a histogram to see which score group most of the students fall into, like in this example above.

Recordings to ways of displaying data, we shouldn’t overlook the effectiveness of line graphs. Line graphs are represented by a group of data points joined together by a straight line. There can be one or more lines to compare how several related things change over time. 

an example of the line graph showing the population of bears from 2017 to 2022

On a line chart’s horizontal axis, you usually have text labels, dates or years, while the vertical axis usually represents the quantity (e.g.: budget, temperature or percentage).

A pictogram graph uses pictures or icons relating to the main topic to visualise a small dataset. The fun combination of colours and illustrations makes it a frequent use at schools.

How to Create Pictographs and Icon Arrays in Visme-6 pictograph maker

Pictograms are a breath of fresh air if you want to stay away from the monotonous line chart or bar chart for a while. However, they can present a very limited amount of data and sometimes they are only there for displays and do not represent real statistics.

If presenting five or more variables in the form of a bar chart is too stuffy then you should try using a radar chart, which is one of the most creative ways to present data.

Radar charts show data in terms of how they compare to each other starting from the same point. Some also call them ‘spider charts’ because each aspect combined looks like a spider web.

a radar chart showing the text scores between two students

Radar charts can be a great use for parents who’d like to compare their child’s grades with their peers to lower their self-esteem. You can see that each angular represents a subject with a score value ranging from 0 to 100. Each student’s score across 5 subjects is highlighted in a different colour.

a radar chart showing the power distribution of a Pokemon

If you think that this method of data presentation somehow feels familiar, then you’ve probably encountered one while playing Pokémon .

A heat map represents data density in colours. The bigger the number, the more colour intense that data will be represented.

a heatmap showing the electoral votes among the states between two candidates

Most U.S citizens would be familiar with this data presentation method in geography. For elections, many news outlets assign a specific colour code to a state, with blue representing one candidate and red representing the other. The shade of either blue or red in each state shows the strength of the overall vote in that state.

a heatmap showing which parts the visitors click on in a website

Another great thing you can use a heat map for is to map what visitors to your site click on. The more a particular section is clicked the ‘hotter’ the colour will turn, from blue to bright yellow to red.

If you present your data in dots instead of chunky bars, you’ll have a scatter plot. 

A scatter plot is a grid with several inputs showing the relationship between two variables. It’s good at collecting seemingly random data and revealing some telling trends.

a scatter plot example showing the relationship between beach visitors each day and the average daily temperature

For example, in this graph, each dot shows the average daily temperature versus the number of beach visitors across several days. You can see that the dots get higher as the temperature increases, so it’s likely that hotter weather leads to more visitors.

5 Data Presentation Mistakes to Avoid

#1 – assume your audience understands what the numbers represent.

You may know all the behind-the-scenes of your data since you’ve worked with them for weeks, but your audience doesn’t.

a sales data board from Looker

Showing without telling only invites more and more questions from your audience, as they have to constantly make sense of your data, wasting the time of both sides as a result.

While showing your data presentations, you should tell them what the data are about before hitting them with waves of numbers first. You can use interactive activities such as polls , word clouds and Q&A sections to assess their understanding of the data and address any confusion beforehand.

#2 – Use the wrong type of chart

Charts such as pie charts must have a total of 100% so if your numbers accumulate to 193% like this example below, you’re definitely doing it wrong.

a bad example of using a pie chart in the 2012 presidential run

Before making a chart, ask yourself: what do I want to accomplish with my data? Do you want to see the relationship between the data sets, show the up and down trends of your data, or see how segments of one thing make up a whole?

Remember, clarity always comes first. Some data visualisations may look cool, but if they don’t fit your data, steer clear of them. 

#3 – Make it 3D

3D is a fascinating graphical presentation example. The third dimension is cool, but full of risks.

what are different types of data presentation

Can you see what’s behind those red bars? Because we can’t either. You may think that 3D charts add more depth to the design, but they can create false perceptions as our eyes see 3D objects closer and bigger than they appear, not to mention they cannot be seen from multiple angles.

#4 – Use different types of charts to compare contents in the same category

what are different types of data presentation

This is like comparing a fish to a monkey. Your audience won’t be able to identify the differences and make an appropriate correlation between the two data sets. 

Next time, stick to one type of data presentation only. Avoid the temptation of trying various data visualisation methods in one go and make your data as accessible as possible.

#5 – Bombard the audience with too much information

The goal of data presentation is to make complex topics much easier to understand, and if you’re bringing too much information to the table, you’re missing the point.

a very complicated data presentation with too much information on the screen

The more information you give, the more time it will take for your audience to process it all. If you want to make your data understandable and give your audience a chance to remember it, keep the information within it to an absolute minimum.

What are the Best Methods of Data Presentation?

Finally, which is the best way to present data?

The answer is…

There is none 😄 Each type of presentation has its own strengths and weaknesses and the one you choose greatly depends on what you’re trying to do. 

For example:

  • Go for a scatter plot if you’re exploring the relationship between different data values, like seeing whether the sales of ice cream go up because of the temperature or because people are just getting more hungry and greedy each day?
  • Go for a line graph if you want to mark a trend over time. 
  • Go for a heat map if you like some fancy visualisation of the changes in a geographical location, or to see your visitors’ behaviour on your website.
  • Go for a pie chart (especially in 3D) if you want to be shunned by others because it was never a good idea👇

example of how a bad pie chart represents the data in a complicated way

Got a question? We've got answers.

What is chart presentation?

When can i use charts for presentation, why should use charts for presentation, what are the 4 graphical methods of presenting data.

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Leah Nguyen

Words that convert, stories that stick. I turn complex ideas into engaging narratives - helping audiences learn, remember, and take action.

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Hey there, fellow data enthusiast!

Welcome to our comprehensive guide on data presentation.

Whether you're an experienced presenter or just starting, this guide will help you present your data like a pro.

We'll dive deep into what data presentation is, why it's crucial, and how to master it. So, let's embark on this data-driven journey together.

What is data presentation?

Data presentation is the art of transforming raw data into a visual format that's easy to understand and interpret. It's like turning numbers and statistics into a captivating story that your audience can quickly grasp. When done right, data presentation can be a game-changer, enabling you to convey complex information effectively.

Why are data presentations important?

Imagine drowning in a sea of numbers and figures. That's how your audience might feel without proper data presentation. Here's why it's essential:

  • Clarity : Data presentations make complex information clear and concise.
  • Engagement : Visuals, such as charts and graphs, grab your audience's attention.
  • Comprehension : Visual data is easier to understand than long, numerical reports.
  • Decision-making : Well-presented data aids informed decision-making.
  • Impact : It leaves a lasting impression on your audience.

Types of data presentation

Now, let's delve into the diverse array of data presentation methods, each with its own unique strengths and applications. We have three primary types of data presentation, and within these categories, numerous specific visualization techniques can be employed to effectively convey your data.

1. Textual presentation

Textual presentation harnesses the power of words and sentences to elucidate and contextualize your data. This method is commonly used to provide a narrative framework for the data, offering explanations, insights, and the broader implications of your findings. It serves as a foundation for a deeper understanding of the data's significance.

2. Tabular presentation

Tabular presentation employs tables to arrange and structure your data systematically. These tables are invaluable for comparing various data groups or illustrating how data evolves over time. They present information in a neat and organized format, facilitating straightforward comparisons and reference points.

3. Graphical presentation

Graphical presentation harnesses the visual impact of charts and graphs to breathe life into your data. Charts and graphs are powerful tools for spotlighting trends, patterns, and relationships hidden within the data. Let's explore some common graphical presentation methods:

  • Bar charts: They are ideal for comparing different categories of data. In this method, each category is represented by a distinct bar, and the height of the bar corresponds to the value it represents. Bar charts provide a clear and intuitive way to discern differences between categories.
  • Pie charts: It excel at illustrating the relative proportions of different data categories. Each category is depicted as a slice of the pie, with the size of each slice corresponding to the percentage of the total value it represents. Pie charts are particularly effective for showcasing the distribution of data.
  • Line graphs: They are the go-to choice when showcasing how data evolves over time. Each point on the line represents a specific value at a particular time period. This method enables viewers to track trends and fluctuations effortlessly, making it perfect for visualizing data with temporal dimensions.
  • Scatter plots: They are the tool of choice when exploring the relationship between two variables. In this method, each point on the plot represents a pair of values for the two variables in question. Scatter plots help identify correlations, outliers, and patterns within data pairs.

The selection of the most suitable data presentation method hinges on the specific dataset and the presentation's objectives. For instance, when comparing sales figures of different products, a bar chart shines in its simplicity and clarity. On the other hand, if your aim is to display how a product's sales have changed over time, a line graph provides the ideal visual narrative.

Additionally, it's crucial to factor in your audience's level of familiarity with data presentations. For a technical audience, more intricate visualization methods may be appropriate. However, when presenting to a general audience, opting for straightforward and easily understandable visuals is often the wisest choice.

In the world of data presentation, choosing the right method is akin to selecting the perfect brush for a masterpiece. Each tool has its place, and understanding when and how to use them is key to crafting compelling and insightful presentations. So, consider your data carefully, align your purpose, and paint a vivid picture that resonates with your audience.

What to include in data presentation

When creating your data presentation, remember these key components:

  • Data points : Clearly state the data points you're presenting.
  • Comparison : Highlight comparisons and trends in your data.
  • Graphical methods : Choose the right chart or graph for your data.
  • Infographics : Use visuals like infographics to make information more digestible.
  • Numerical values : Include numerical values to support your visuals.
  • Qualitative information : Explain the significance of the data.
  • Source citation : Always cite your data sources.

How to structure an effective data presentation

Creating a well-structured data presentation is not just important; it's the backbone of a successful presentation. Here's a step-by-step guide to help you craft a compelling and organized presentation that captivates your audience:

1. Know your audience

Understanding your audience is paramount. Consider their needs, interests, and existing knowledge about your topic. Tailor your presentation to their level of understanding, ensuring that it resonates with them on a personal level. Relevance is the key.

2. Have a clear message

Every effective data presentation should convey a clear and concise message. Determine what you want your audience to learn or take away from your presentation, and make sure your message is the guiding light throughout your presentation. Ensure that all your data points align with and support this central message.

3. Tell a compelling story

Human beings are naturally wired to remember stories. Incorporate storytelling techniques into your presentation to make your data more relatable and memorable. Your data can be the backbone of a captivating narrative, whether it's about a trend, a problem, or a solution. Take your audience on a journey through your data.

4. Leverage visuals

Visuals are a powerful tool in data presentation. They make complex information accessible and engaging. Utilize charts, graphs, and images to illustrate your points and enhance the visual appeal of your presentation. Visuals should not just be an accessory; they should be an integral part of your storytelling.

5. Be clear and concise

Avoid jargon or technical language that your audience may not comprehend. Use plain language and explain your data points clearly. Remember, clarity is king. Each piece of information should be easy for your audience to digest.

6. Practice your delivery

Practice makes perfect. Rehearse your presentation multiple times before the actual delivery. This will help you deliver it smoothly and confidently, reducing the chances of stumbling over your words or losing track of your message.

A basic structure for an effective data presentation

Armed with a comprehensive comprehension of how to construct a compelling data presentation, you can now utilize this fundamental template for guidance:

In the introduction, initiate your presentation by introducing both yourself and the topic at hand. Clearly articulate your main message or the fundamental concept you intend to communicate.

Moving on to the body of your presentation, organize your data in a coherent and easily understandable sequence. Employ visuals generously to elucidate your points and weave a narrative that enhances the overall story. Ensure that the arrangement of your data aligns with and reinforces your central message.

As you approach the conclusion, succinctly recapitulate your key points and emphasize your core message once more. Conclude by leaving your audience with a distinct and memorable takeaway, ensuring that your presentation has a lasting impact.

Additional tips for enhancing your data presentation

To take your data presentation to the next level, consider these additional tips:

  • Consistent design : Maintain a uniform design throughout your presentation. This not only enhances visual appeal but also aids in seamless comprehension.
  • High-quality visuals : Ensure that your visuals are of high quality, easy to read, and directly relevant to your topic.
  • Concise text : Avoid overwhelming your slides with excessive text. Focus on the most critical points, using visuals to support and elaborate.
  • Anticipate questions : Think ahead about the questions your audience might pose. Be prepared with well-thought-out answers to foster productive discussions.

By following these guidelines, you can structure an effective data presentation that not only informs but also engages and inspires your audience. Remember, a well-structured presentation is the bridge that connects your data to your audience's understanding and appreciation.

Do’s and don'ts on a data presentation

  • Use visuals : Incorporate charts and graphs to enhance understanding.
  • Keep it simple : Avoid clutter and complexity.
  • Highlight key points : Emphasize crucial data.
  • Engage the audience : Encourage questions and discussions.
  • Practice : Rehearse your presentation.

Don'ts:

  • Overload with data : Less is often more; don't overwhelm your audience.
  • Fit Unrelated data : Stay on topic; don't include irrelevant information.
  • Neglect the audience : Ensure your presentation suits your audience's level of expertise.
  • Read word-for-word : Avoid reading directly from slides.
  • Lose focus : Stick to your presentation's purpose.

Summarizing key takeaways

  • Definition : Data presentation is the art of visualizing complex data for better understanding.
  • Importance : Data presentations enhance clarity, engage the audience, aid decision-making, and leave a lasting impact.
  • Types : Textual, Tabular, and Graphical presentations offer various ways to present data.
  • Choosing methods : Select the right method based on data, audience, and purpose.
  • Components : Include data points, comparisons, visuals, infographics, numerical values, and source citations.
  • Structure : Know your audience, have a clear message, tell a compelling story, use visuals, be concise, and practice.
  • Do's and don'ts : Do use visuals, keep it simple, highlight key points, engage the audience, and practice. Don't overload with data, include unrelated information, neglect the audience's expertise, read word-for-word, or lose focus.

1. What is data presentation, and why is it important in 2023?

Data presentation is the process of visually representing data sets to convey information effectively to an audience. In an era where the amount of data generated is vast, visually presenting data using methods such as diagrams, graphs, and charts has become crucial. By simplifying complex data sets, presentation of the data may helps your audience quickly grasp much information without drowning in a sea of chart's, analytics, facts and figures.

2. What are some common methods of data presentation?

There are various methods of data presentation, including graphs and charts, histograms, and cumulative frequency polygons. Each method has its strengths and is often used depending on the type of data you're using and the message you want to convey. For instance, if you want to show data over time, try using a line graph. If you're presenting geographical data, consider to use a heat map.

3. How can I ensure that my data presentation is clear and readable?

To ensure that your data presentation is clear and readable, pay attention to the design and labeling of your charts. Don't forget to label the axes appropriately, as they are critical for understanding the values they represent. Don't fit all the information in one slide or in a single paragraph. Presentation software like Prezent and PowerPoint can help you simplify your vertical axis, charts and tables, making them much easier to understand.

4. What are some common mistakes presenters make when presenting data?

One common mistake is trying to fit too much data into a single chart, which can distort the information and confuse the audience. Another mistake is not considering the needs of the audience. Remember that your audience won't have the same level of familiarity with the data as you do, so it's essential to present the data effectively and respond to questions during a Q&A session.

5. How can I use data visualization to present important data effectively on platforms like LinkedIn?

When presenting data on platforms like LinkedIn, consider using eye-catching visuals like bar graphs or charts. Use concise captions and e.g., examples to highlight the single most important information in your data report. Visuals, such as graphs and tables, can help you stand out in the sea of textual content, making your data presentation more engaging and shareable among your LinkedIn connections.

Create your data presentation with prezent

Prezent can be a valuable tool for creating data presentations. Here's how Prezent can help you in this regard:

  • Time savings : Prezent saves up to 70% of presentation creation time, allowing you to focus on data analysis and insights.
  • On-brand consistency : Ensure 100% brand alignment with Prezent's brand-approved designs for professional-looking data presentations.
  • Effortless collaboration : Real-time sharing and collaboration features make it easy for teams to work together on data presentations.
  • Data storytelling : Choose from 50+ storylines to effectively communicate data insights and engage your audience.
  • Personalization : Create tailored data presentations that resonate with your audience's preferences, enhancing the impact of your data.

In summary, Prezent streamlines the process of creating data presentations by offering time-saving features, ensuring brand consistency, promoting collaboration, and providing tools for effective data storytelling. Whether you need to present data to clients, stakeholders, or within your organization, Prezent can significantly enhance your presentation-making process.

So, go ahead, present your data with confidence, and watch your audience be wowed by your expertise.

Thank you for joining us on this data-driven journey. Stay tuned for more insights, and remember, data presentation is your ticket to making numbers come alive!

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  • Korean J Anesthesiol
  • v.70(3); 2017 Jun

Statistical data presentation

1 Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Korea.

Sangseok Lee

2 Department of Anesthesiology and Pain Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea.

Data are usually collected in a raw format and thus the inherent information is difficult to understand. Therefore, raw data need to be summarized, processed, and analyzed. However, no matter how well manipulated, the information derived from the raw data should be presented in an effective format, otherwise, it would be a great loss for both authors and readers. In this article, the techniques of data and information presentation in textual, tabular, and graphical forms are introduced. Text is the principal method for explaining findings, outlining trends, and providing contextual information. A table is best suited for representing individual information and represents both quantitative and qualitative information. A graph is a very effective visual tool as it displays data at a glance, facilitates comparison, and can reveal trends and relationships within the data such as changes over time, frequency distribution, and correlation or relative share of a whole. Text, tables, and graphs for data and information presentation are very powerful communication tools. They can make an article easy to understand, attract and sustain the interest of readers, and efficiently present large amounts of complex information. Moreover, as journal editors and reviewers glance at these presentations before reading the whole article, their importance cannot be ignored.

Introduction

Data are a set of facts, and provide a partial picture of reality. Whether data are being collected with a certain purpose or collected data are being utilized, questions regarding what information the data are conveying, how the data can be used, and what must be done to include more useful information must constantly be kept in mind.

Since most data are available to researchers in a raw format, they must be summarized, organized, and analyzed to usefully derive information from them. Furthermore, each data set needs to be presented in a certain way depending on what it is used for. Planning how the data will be presented is essential before appropriately processing raw data.

First, a question for which an answer is desired must be clearly defined. The more detailed the question is, the more detailed and clearer the results are. A broad question results in vague answers and results that are hard to interpret. In other words, a well-defined question is crucial for the data to be well-understood later. Once a detailed question is ready, the raw data must be prepared before processing. These days, data are often summarized, organized, and analyzed with statistical packages or graphics software. Data must be prepared in such a way they are properly recognized by the program being used. The present study does not discuss this data preparation process, which involves creating a data frame, creating/changing rows and columns, changing the level of a factor, categorical variable, coding, dummy variables, variable transformation, data transformation, missing value, outlier treatment, and noise removal.

We describe the roles and appropriate use of text, tables, and graphs (graphs, plots, or charts), all of which are commonly used in reports, articles, posters, and presentations. Furthermore, we discuss the issues that must be addressed when presenting various kinds of information, and effective methods of presenting data, which are the end products of research, and of emphasizing specific information.

Data Presentation

Data can be presented in one of the three ways:

–as text;

–in tabular form; or

–in graphical form.

Methods of presentation must be determined according to the data format, the method of analysis to be used, and the information to be emphasized. Inappropriately presented data fail to clearly convey information to readers and reviewers. Even when the same information is being conveyed, different methods of presentation must be employed depending on what specific information is going to be emphasized. A method of presentation must be chosen after carefully weighing the advantages and disadvantages of different methods of presentation. For easy comparison of different methods of presentation, let us look at a table ( Table 1 ) and a line graph ( Fig. 1 ) that present the same information [ 1 ]. If one wishes to compare or introduce two values at a certain time point, it is appropriate to use text or the written language. However, a table is the most appropriate when all information requires equal attention, and it allows readers to selectively look at information of their own interest. Graphs allow readers to understand the overall trend in data, and intuitively understand the comparison results between two groups. One thing to always bear in mind regardless of what method is used, however, is the simplicity of presentation.

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Values are expressed as mean ± SD. Group C: normal saline, Group D: dexmedetomidine. SBP: systolic blood pressure, DBP: diastolic blood pressure, MBP: mean blood pressure, HR: heart rate. * P < 0.05 indicates a significant increase in each group, compared with the baseline values. † P < 0.05 indicates a significant decrease noted in Group D, compared with the baseline values. ‡ P < 0.05 indicates a significant difference between the groups.

Text presentation

Text is the main method of conveying information as it is used to explain results and trends, and provide contextual information. Data are fundamentally presented in paragraphs or sentences. Text can be used to provide interpretation or emphasize certain data. If quantitative information to be conveyed consists of one or two numbers, it is more appropriate to use written language than tables or graphs. For instance, information about the incidence rates of delirium following anesthesia in 2016–2017 can be presented with the use of a few numbers: “The incidence rate of delirium following anesthesia was 11% in 2016 and 15% in 2017; no significant difference of incidence rates was found between the two years.” If this information were to be presented in a graph or a table, it would occupy an unnecessarily large space on the page, without enhancing the readers' understanding of the data. If more data are to be presented, or other information such as that regarding data trends are to be conveyed, a table or a graph would be more appropriate. By nature, data take longer to read when presented as texts and when the main text includes a long list of information, readers and reviewers may have difficulties in understanding the information.

Table presentation

Tables, which convey information that has been converted into words or numbers in rows and columns, have been used for nearly 2,000 years. Anyone with a sufficient level of literacy can easily understand the information presented in a table. Tables are the most appropriate for presenting individual information, and can present both quantitative and qualitative information. Examples of qualitative information are the level of sedation [ 2 ], statistical methods/functions [ 3 , 4 ], and intubation conditions [ 5 ].

The strength of tables is that they can accurately present information that cannot be presented with a graph. A number such as “132.145852” can be accurately expressed in a table. Another strength is that information with different units can be presented together. For instance, blood pressure, heart rate, number of drugs administered, and anesthesia time can be presented together in one table. Finally, tables are useful for summarizing and comparing quantitative information of different variables. However, the interpretation of information takes longer in tables than in graphs, and tables are not appropriate for studying data trends. Furthermore, since all data are of equal importance in a table, it is not easy to identify and selectively choose the information required.

For a general guideline for creating tables, refer to the journal submission requirements 1) .

Heat maps for better visualization of information than tables

Heat maps help to further visualize the information presented in a table by applying colors to the background of cells. By adjusting the colors or color saturation, information is conveyed in a more visible manner, and readers can quickly identify the information of interest ( Table 2 ). Software such as Excel (in Microsoft Office, Microsoft, WA, USA) have features that enable easy creation of heat maps through the options available on the “conditional formatting” menu.

All numbers were created by the author. SBP: systolic blood pressure, DBP: diastolic blood pressure, MBP: mean blood pressure, HR: heart rate.

Graph presentation

Whereas tables can be used for presenting all the information, graphs simplify complex information by using images and emphasizing data patterns or trends, and are useful for summarizing, explaining, or exploring quantitative data. While graphs are effective for presenting large amounts of data, they can be used in place of tables to present small sets of data. A graph format that best presents information must be chosen so that readers and reviewers can easily understand the information. In the following, we describe frequently used graph formats and the types of data that are appropriately presented with each format with examples.

Scatter plot

Scatter plots present data on the x - and y -axes and are used to investigate an association between two variables. A point represents each individual or object, and an association between two variables can be studied by analyzing patterns across multiple points. A regression line is added to a graph to determine whether the association between two variables can be explained or not. Fig. 2 illustrates correlations between pain scoring systems that are currently used (PSQ, Pain Sensitivity Questionnaire; PASS, Pain Anxiety Symptoms Scale; PCS, Pain Catastrophizing Scale) and Geop-Pain Questionnaire (GPQ) with the correlation coefficient, R, and regression line indicated on the scatter plot [ 6 ]. If multiple points exist at an identical location as in this example ( Fig. 2 ), the correlation level may not be clear. In this case, a correlation coefficient or regression line can be added to further elucidate the correlation.

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Bar graph and histogram

A bar graph is used to indicate and compare values in a discrete category or group, and the frequency or other measurement parameters (i.e. mean). Depending on the number of categories, and the size or complexity of each category, bars may be created vertically or horizontally. The height (or length) of a bar represents the amount of information in a category. Bar graphs are flexible, and can be used in a grouped or subdivided bar format in cases of two or more data sets in each category. Fig. 3 is a representative example of a vertical bar graph, with the x -axis representing the length of recovery room stay and drug-treated group, and the y -axis representing the visual analog scale (VAS) score. The mean and standard deviation of the VAS scores are expressed as whiskers on the bars ( Fig. 3 ) [ 7 ].

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By comparing the endpoints of bars, one can identify the largest and the smallest categories, and understand gradual differences between each category. It is advised to start the x - and y -axes from 0. Illustration of comparison results in the x - and y -axes that do not start from 0 can deceive readers' eyes and lead to overrepresentation of the results.

One form of vertical bar graph is the stacked vertical bar graph. A stack vertical bar graph is used to compare the sum of each category, and analyze parts of a category. While stacked vertical bar graphs are excellent from the aspect of visualization, they do not have a reference line, making comparison of parts of various categories challenging ( Fig. 4 ) [ 8 ].

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A pie chart, which is used to represent nominal data (in other words, data classified in different categories), visually represents a distribution of categories. It is generally the most appropriate format for representing information grouped into a small number of categories. It is also used for data that have no other way of being represented aside from a table (i.e. frequency table). Fig. 5 illustrates the distribution of regular waste from operation rooms by their weight [ 8 ]. A pie chart is also commonly used to illustrate the number of votes each candidate won in an election.

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Line plot with whiskers

A line plot is useful for representing time-series data such as monthly precipitation and yearly unemployment rates; in other words, it is used to study variables that are observed over time. Line graphs are especially useful for studying patterns and trends across data that include climatic influence, large changes or turning points, and are also appropriate for representing not only time-series data, but also data measured over the progression of a continuous variable such as distance. As can be seen in Fig. 1 , mean and standard deviation of systolic blood pressure are indicated for each time point, which enables readers to easily understand changes of systolic pressure over time [ 1 ]. If data are collected at a regular interval, values in between the measurements can be estimated. In a line graph, the x-axis represents the continuous variable, while the y-axis represents the scale and measurement values. It is also useful to represent multiple data sets on a single line graph to compare and analyze patterns across different data sets.

Box and whisker chart

A box and whisker chart does not make any assumptions about the underlying statistical distribution, and represents variations in samples of a population; therefore, it is appropriate for representing nonparametric data. AA box and whisker chart consists of boxes that represent interquartile range (one to three), the median and the mean of the data, and whiskers presented as lines outside of the boxes. Whiskers can be used to present the largest and smallest values in a set of data or only a part of the data (i.e. 95% of all the data). Data that are excluded from the data set are presented as individual points and are called outliers. The spacing at both ends of the box indicates dispersion in the data. The relative location of the median demonstrated within the box indicates skewness ( Fig. 6 ). The box and whisker chart provided as an example represents calculated volumes of an anesthetic, desflurane, consumed over the course of the observation period ( Fig. 7 ) [ 9 ].

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Three-dimensional effects

Most of the recently introduced statistical packages and graphics software have the three-dimensional (3D) effect feature. The 3D effects can add depth and perspective to a graph. However, since they may make reading and interpreting data more difficult, they must only be used after careful consideration. The application of 3D effects on a pie chart makes distinguishing the size of each slice difficult. Even if slices are of similar sizes, slices farther from the front of the pie chart may appear smaller than the slices closer to the front ( Fig. 8 ).

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Drawing a graph: example

Finally, we explain how to create a graph by using a line graph as an example ( Fig. 9 ). In Fig. 9 , the mean values of arterial pressure were randomly produced and assumed to have been measured on an hourly basis. In many graphs, the x- and y-axes meet at the zero point ( Fig. 9A ). In this case, information regarding the mean and standard deviation of mean arterial pressure measurements corresponding to t = 0 cannot be conveyed as the values overlap with the y-axis. The data can be clearly exposed by separating the zero point ( Fig. 9B ). In Fig. 9B , the mean and standard deviation of different groups overlap and cannot be clearly distinguished from each other. Separating the data sets and presenting standard deviations in a single direction prevents overlapping and, therefore, reduces the visual inconvenience. Doing so also reduces the excessive number of ticks on the y-axis, increasing the legibility of the graph ( Fig. 9C ). In the last graph, different shapes were used for the lines connecting different time points to further allow the data to be distinguished, and the y-axis was shortened to get rid of the unnecessary empty space present in the previous graphs ( Fig. 9D ). A graph can be made easier to interpret by assigning each group to a different color, changing the shape of a point, or including graphs of different formats [ 10 ]. The use of random settings for the scale in a graph may lead to inappropriate presentation or presentation of data that can deceive readers' eyes ( Fig. 10 ).

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Owing to the lack of space, we could not discuss all types of graphs, but have focused on describing graphs that are frequently used in scholarly articles. We have summarized the commonly used types of graphs according to the method of data analysis in Table 3 . For general guidelines on graph designs, please refer to the journal submission requirements 2) .

Conclusions

Text, tables, and graphs are effective communication media that present and convey data and information. They aid readers in understanding the content of research, sustain their interest, and effectively present large quantities of complex information. As journal editors and reviewers will scan through these presentations before reading the entire text, their importance cannot be disregarded. For this reason, authors must pay as close attention to selecting appropriate methods of data presentation as when they were collecting data of good quality and analyzing them. In addition, having a well-established understanding of different methods of data presentation and their appropriate use will enable one to develop the ability to recognize and interpret inappropriately presented data or data presented in such a way that it deceives readers' eyes [ 11 ].

<Appendix>

Output for presentation.

Discovery and communication are the two objectives of data visualization. In the discovery phase, various types of graphs must be tried to understand the rough and overall information the data are conveying. The communication phase is focused on presenting the discovered information in a summarized form. During this phase, it is necessary to polish images including graphs, pictures, and videos, and consider the fact that the images may look different when printed than how appear on a computer screen. In this appendix, we discuss important concepts that one must be familiar with to print graphs appropriately.

The KJA asks that pictures and images meet the following requirement before submission 3)

“Figures and photographs should be submitted as ‘TIFF’ files. Submit files of figures and photographs separately from the text of the paper. Width of figure should be 84 mm (one column). Contrast of photos or graphs should be at least 600 dpi. Contrast of line drawings should be at least 1,200 dpi. The Powerpoint file (ppt, pptx) is also acceptable.”

Unfortunately, without sufficient knowledge of computer graphics, it is not easy to understand the submission requirement above. Therefore, it is necessary to develop an understanding of image resolution, image format (bitmap and vector images), and the corresponding file specifications.

Resolution is often mentioned to describe the quality of images containing graphs or CT/MRI scans, and video files. The higher the resolution, the clearer and closer to reality the image is, while the opposite is true for low resolutions. The most representative unit used to describe a resolution is “dpi” (dots per inch): this literally translates to the number of dots required to constitute 1 inch. The greater the number of dots, the higher the resolution. The KJA submission requirements recommend 600 dpi for images, and 1,200 dpi 4) for graphs. In other words, resolutions in which 600 or 1,200 dots constitute one inch are required for submission.

There are requirements for the horizontal length of an image in addition to the resolution requirements. While there are no requirements for the vertical length of an image, it must not exceed the vertical length of a page. The width of a column on one side of a printed page is 84 mm, or 3.3 inches (84/25.4 mm ≒ 3.3 inches). Therefore, a graph must have a resolution in which 1,200 dots constitute 1 inch, and have a width of 3.3 inches.

Bitmap and Vector

Methods of image construction are important. Bitmap images can be considered as images drawn on section paper. Enlarging the image will enlarge the picture along with the grid, resulting in a lower resolution; in other words, aliasing occurs. On the other hand, reducing the size of the image will reduce the size of the picture, while increasing the resolution. In other words, resolution and the size of an image are inversely proportionate to one another in bitmap images, and it is a drawback of bitmap images that resolution must be considered when adjusting the size of an image. To enlarge an image while maintaining the same resolution, the size and resolution of the image must be determined before saving the image. An image that has already been created cannot avoid changes to its resolution according to changes in size. Enlarging an image while maintaining the same resolution will increase the number of horizontal and vertical dots, ultimately increasing the number of pixels 5) of the image, and the file size. In other words, the file size of a bitmap image is affected by the size and resolution of the image (file extensions include JPG [JPEG] 6) , PNG 7) , GIF 8) , and TIF [TIFF] 9) . To avoid this complexity, the width of an image can be set to 4 inches and its resolution to 900 dpi to satisfy the submission requirements of most journals [ 12 ].

Vector images overcome the shortcomings of bitmap images. Vector images are created based on mathematical operations of line segments and areas between different points, and are not affected by aliasing or pixelation. Furthermore, they result in a smaller file size that is not affected by the size of the image. They are commonly used for drawings and illustrations (file extensions include EPS 10) , CGM 11) , and SVG 12) ).

Finally, the PDF 13) is a file format developed by Adobe Systems (Adobe Systems, CA, USA) for electronic documents, and can contain general documents, text, drawings, images, and fonts. They can also contain bitmap and vector images. While vector images are used by researchers when working in Powerpoint, they are saved as 960 × 720 dots when saved in TIFF format in Powerpoint. This results in a resolution that is inappropriate for printing on a paper medium. To save high-resolution bitmap images, the image must be saved as a PDF file instead of a TIFF, and the saved PDF file must be imported into an imaging processing program such as Photoshop™(Adobe Systems, CA, USA) to be saved in TIFF format [ 12 ].

1) Instructions to authors in KJA; section 5-(9) Table; https://ekja.org/index.php?body=instruction

2) Instructions to Authors in KJA; section 6-1)-(10) Figures and illustrations in Manuscript preparation; https://ekja.org/index.php?body=instruction

3) Instructions to Authors in KJA; section 6-1)-(10) Figures and illustrations in Manuscript preparation; https://ekja.org/index.php?body=instruction

4) Resolution; in KJA, it is represented by “contrast.”

5) Pixel is a minimum unit of an image and contains information of a dot and color. It is derived by multiplying the number of vertical and horizontal dots regardless of image size. For example, Full High Definition (FHD) monitor has 1920 × 1080 dots ≒ 2.07 million pixel.

6) Joint Photographic Experts Group.

7) Portable Network Graphics.

8) Graphics Interchange Format

9) Tagged Image File Format; TIFF

10) Encapsulated PostScript.

11) Computer Graphics Metafile.

12) Scalable Vector Graphics.

13) Portable Document Format.

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Present Your Data Like a Pro

  • Joel Schwartzberg

what are different types of data presentation

Demystify the numbers. Your audience will thank you.

While a good presentation has data, data alone doesn’t guarantee a good presentation. It’s all about how that data is presented. The quickest way to confuse your audience is by sharing too many details at once. The only data points you should share are those that significantly support your point — and ideally, one point per chart. To avoid the debacle of sheepishly translating hard-to-see numbers and labels, rehearse your presentation with colleagues sitting as far away as the actual audience would. While you’ve been working with the same chart for weeks or months, your audience will be exposed to it for mere seconds. Give them the best chance of comprehending your data by using simple, clear, and complete language to identify X and Y axes, pie pieces, bars, and other diagrammatic elements. Try to avoid abbreviations that aren’t obvious, and don’t assume labeled components on one slide will be remembered on subsequent slides. Every valuable chart or pie graph has an “Aha!” zone — a number or range of data that reveals something crucial to your point. Make sure you visually highlight the “Aha!” zone, reinforcing the moment by explaining it to your audience.

With so many ways to spin and distort information these days, a presentation needs to do more than simply share great ideas — it needs to support those ideas with credible data. That’s true whether you’re an executive pitching new business clients, a vendor selling her services, or a CEO making a case for change.

what are different types of data presentation

  • JS Joel Schwartzberg oversees executive communications for a major national nonprofit, is a professional presentation coach, and is the author of Get to the Point! Sharpen Your Message and Make Your Words Matter and The Language of Leadership: How to Engage and Inspire Your Team . You can find him on LinkedIn and X. TheJoelTruth

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Data Presentation Techniques that Make an Impact

Create beautiful charts & infographics get started, 10.05.2016 by anete ezera.

Presenting data doesn’t need to be boring. In fact, it is a great way to spice up your presentations and share important facts and figures with your audience. Data has the power to be engaging, persuasive and memorable.

If you have a compelling story to tell with data, you should present it in a clear and powerful way. We will help you get started with a few effective data presentation techniques!

If you’d like more information about designing great presentations, download our new eBook ‘How to Design PowerPoint Presentations that Pack a Punch in 5 Easy Steps.’

Get the Complete Guide!

What Presentations Benefit from Data?

Data doesn’t necessarily make all presentations better, but certain types of presentations are prime for the incorporation of data visualizations:

  • Sales Reports
  • PR and Marketing Research
  • Marketing and Advertising Campaigns
  • Executive and CEO Presentations
  • Educational Reports
  • Political Speeches
  • Annual Reports
  • Shareholder Presentations
  • Financial Reports
  • Product Launches, and more!

Why Use Charts in Presentations?

Visuals make information stick in our brains . A study from the Wharton School of Business found that 67% of the audience surveyed were persuaded by verbal presentations that had accompanying visuals. Charts are great visual aids for multiple reasons:

  • Charts are easy to read
  • Charts are visually appealing
  • Charts simplify complex information
  • Charts make it possible to quickly make comparisons and spot trends
  • Charts are memorable and make an impact
  • Charts give your presentation credibility

How to Add Data to Your Presentation

1) define your message.

Before you can even think about adding data to your presentation, you need to ask yourself, ‘what story am I trying to tell?’ Once you have a concrete idea of what your message is, you’ll have an easier time crafting the right visualization to share with your audience.

2) Clean and Organize Your Data

Now that you know what point you want to make with your data, it’s time to make sure your numbers are ready to be visualized.   Every good data visualization starts with good data. Make sure your spreadsheet is formatted and labeled exactly how you want it. Think about the message you want to share with your data and get rid of anything that doesn’t help you tell your story.

Data that is clean and organized is easier to display and analyze. Here are five awesome free data analysis tools to help you extract, clean, and share your data.

3) Pick the Right Chart Type

We can’t emphasize enough how important it is to make sure you pick the right chart type for the data you want to present. While your data might technically work with multiple chart types, you need to pick the one that ensures your message is clear, accurate, and concise.

chart types

4) Simplicity is Key

Charts and graphs turn complex ideas or data sets into easy-to-understand visual concepts. Remember that your data is the star of the show, so keep it simple. Avoid visual clutter, excessive text, poor color selection, and unnecessary animations. Make sure your legend and data labels are printed in a large, visible font. You don’t want your audience to get distracted. Less is more!

5) Create a Narrative

People understand stories better than they understand spreadsheets. Craft a compelling story around your data to make it memorable. Find a way to drive emotion from the numbers. Give your audience something they can relate to and resonate with. Data visualization speaker Bill Shander offers five tips to make you a better data storyteller. 

6) Visualize Data with Infogram

Before you add data to your presentation you need to visualize it. While many presentation tools allow you to create charts , they often leave much to be desired. Infogram makes it easy to create beautiful, engaging data visualizations your audience won’t forget.

You can embed interactive and responsive data visualizations into your presentations if you’re using Bunkr or any other HTML based presentation platform. Or, if you upgrade to one of our paid plans , you can download static versions of your charts and graphs to enhance your work. You can even make the background of PNG downloads transparent so they slip seamlessly into your presentation.

Infogram_transparent_embed

Would you like to experience the full power of  data visualization ? Try Infogram for Teams or Enterprise for free! With a Team or Enterprise account, you can create up to 10,000+ projects, collaborate with your team in real time, use our engagement analytics feature, and more. Request your free demo  here .

7) Make a Handout

Leave your audience with a physical or virtual copy of your charts. This makes it possible for them to look at the numbers more closely after your presentation. It’s also nice to include extra information, beyond what you covered, in case someone wants to delve deeper into the material.

Now that you know how to add data to your presentations, it’s time to learn how to design a PowerPoint that really gets people talking. Download our latest eBook ‘How to Design PowerPoint Presentations that Pack a Punch in 5 Easy Steps’ – for free!

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what are different types of data presentation

Top 5 Easy-to-Follow Data Presentation Examples

You’ll agree when we say that poring through numbers is tedious at best and mentally exhausting at worst.

And this is where data presentation examples come in.

data presentation examples

Charts come in and distill data into meaningful insights. And this saves tons of hours, which you can use to relax or execute other tasks. Besides, when creating data stories, you need charts that communicate insights with clarity.

There’re 5 solid and reliable data presentation methods: textual, statistical data presentation, measures of dispersion, tabular, and graphical data representation.

Besides, some of the tested and proven charts for data presentation include:

  • Double Bar Graph
  • Slope Chart
  • Treemap Charts
  • Radar Chart
  • Sankey Chart

There’re visualization tools that produce simple, insightful, and ready-made data presentation charts. Yes, you read that right. These tools create charts that complement data stories seamlessly.

Remember, without visualizing data to extract insights, chances of creating a compelling narrative will go down.

Table of Content:

What is data presentation, top 5 data presentation examples:, how to generate sankey chart in excel for data presentation, importance of data presentation in business, benefits of data presentation, what are the top 5 methods of data presentation.

Data presentation is the process of using charts and graphs formats to display insights into data. The insights could be:

  • Relationship
  • Trend and patterns

Data Analysis  and  Data Presentation  have a practical implementation in every possible field. It can range from academic studies, commercial, industrial , and marketing activities to professional practices .

In its raw form, data can be extremely complicated to decipher. Data presentation examples are an important step toward breaking down data into understandable charts or graphs.

You can use tools (which we’ll talk about later) to analyze raw data.

Once the required information is obtained from the data, the next logical step is to present the data in a graphical presentation.

The presentation is the key to success.

Once you’ve extracted actionable insights, you can craft a compelling data story. Keep reading because we’ll address the following in the coming section: the importance of data presentation in business.

Let’s take a look at the five data presentation examples below:

1. Double Bar Graph

data presentation examples using double bar graph

A Double Bar Chart displays more than one data series in clustered horizontal columns.

Each data series shares the same axis labels, so horizontal bars are grouped by category.

Bars directly compare multiple series in a given category. The chart is amazingly easy to read and interpret, even for a non-technical audience.

2. Slope Chart

Slope Charts are simple graphs that quickly and directly show  transitions, changes over time, absolute values, and even rankings .

data presentation examples using slope chart

Besides, they’re also called Slope Graphs.

This is one of the data presentation examples you can use to show the before and after story of variables in your data.

Slope Graphs can be useful when you have two time periods or points of comparison and want to show relative increases and decreases quickly across various categories between two data points.

Take a look at the table below. Can you provide coherent and actionable insights into the table below?

Notice the difference after visualizing the table. You can easily tell the performance of individual segments in:

  • Macy’s Store

data presentation examples using treemap chart

4. Radar Chart

Radar Chart is also known as Spider Chart or Spider Web Chart. A radar chart is very helpful to visualize the comparison between multiple categories and variables.

data presentation examples using sankey chart

A radar Chart is one of the data presentation examples you can use to compare data of two different time ranges e.g. Current vs Previous. Radar Chart with different scales makes it easy for you to identify trends, patterns, and outliers in your data. You can also use Radar Chart to visualize the data of Polar graph equations.

5. Sankey Chart

data presentation examples using sankey chart

You can use Sankey Chart to visualize data with flow-like attributes, such as material, energy, cost, etc.

This chart draws the reader’s attention to the enormous flows, the largest consumer, the major losses , and other insights.

The aforementioned visualization design is one of the data presentation examples that use links and nodes to uncover hidden insights into relationships between critical metrics.

The size of a node is directly proportionate to the quantity of the data point under review.

So how can you access the data presentation examples (highlighted above)?

Excel is one of the most used tools for visualizing data because it’s easy to use. 

However, you cannot access ready-made and visually appealing data presentation charts for storytelling. But this does not mean you should ditch this freemium data visualization tool.

Did you know you can supercharge your Excel with add-ins to access visually stunning and ready-to-go data presentation charts?

Yes, you can increase the functionality of your Excel and access ready-made data presentation examples for your data stories.

The add-on we recommend you to use is ChartExpo.

What is ChartExpo?

We recommend this tool (ChartExpo) because it’s super easy to use.

You don’t need to take programming night classes to extract insights from your data. ChartExpo is more of a ‘drag-and-drop tool,’ which means you’ll only need to scroll your mouse and fill in respective metrics and dimensions in your data.

ChartExpo comes with a 7-day free trial period.

The tool produces charts that are incredibly easy to read and interpret . And it allows you to save charts in the world’s most recognized formats, namely PNG and JPG.

In the coming section, we’ll show you how to use ChartExpo to visualize your data with one of the data presentation examples (Sankey).

what are different types of data presentation

  To install ChartExpo add-in into your Excel, click this link .

  • Open your Excel and paste the table above.
  • Click the My Apps button.

insert chartexpo in excel

  • Then select ChartExpo and click on  INSERT, as shown below.

open chartexpo in excel

  • Click the Search Box and type “Sankey Chart” .

search chart in excel

  • Once the chart pops up, click on its icon to get started.

create chart in excel

  • Select the sheet holding your data and click the Create Chart from Selection button.

edit chart in excel

How to Edit the Sankey Chart?

  • Click the Edit Chart button, as shown above.

edit chart headert properties in excel

  • Once the Chart Header Properties window shows, click the Line 1 box and fill in your title.

select node color in excel

  • To change the color of the nodes, click the pen-like icons on the nodes.
  • Once the color window shows, select the Node Color and then the Apply button.

save chart in excel

  • Save your changes by clicking the Apply button.
  • Check out the final chart below.

data presentation examples using sankey graph

Data presentation examples are vital, especially when crafting data stories for the top management. Top management can use data presentation charts, such as Sankey, as a backdrop for their decision.

Presentation charts, maps, and graphs are powerful because they simplify data by making it understandable & readable at the same time. Besides, they make data stories compelling and irresistible to target audiences.

Big files with numbers are usually hard to read and make it difficult to spot patterns easily. However, many businesses believe that developing visual reports focused on creating stories around data is unnecessary; they think that the data alone should be sufficient for decision-making.

Visualizing supports this and lightens the decision-making process.

Luckily, there are innovative applications you can use to visualize all the data your company has into dashboards, graphs, and reports. Data visualization helps transform your numbers into an engaging story with details and patterns.

Check out more benefits of data presentation examples below:

1. Easy to understand

You can interpret vast quantities of data clearly and cohesively to draw insights, thanks to graphic representations.

Using data presentation examples, such as charts, managers and decision-makers can easily create and rapidly consume key metrics.

If any of the aforementioned metrics have anomalies — ie. sales are significantly down in one region — decision-makers will easily dig into the data to diagnose the problem.

2. Spot patterns

Data visualization can help you to do trend analysis and respond rapidly on the grounds of what you see.

Such patterns make more sense when graphically represented; because charts make it easier to identify correlated parameters.

3. Data Narratives

You can use data presentation charts, such as Sankey, to build dashboards and turn them into stories.

Data storytelling can help you connect with potential readers and audiences on an emotional level.

4. Speed up the decision-making process

We naturally process visual images 60,000 times faster than text. A graph, chart, or other visual representation of data is more comfortable for our brain to process.

Thanks to our ability to easily interpret visual content, data presentation examples can dramatically improve the speed of decision-making processes.

Take a look at the table below?

Can you give reliable insights into the table above?

Keep reading because we’ll explore easy-to-follow data presentation examples in the coming section. Also, we’ll address the following question: what are the top 5 methods of data presentation?

1. Textual Ways of Presenting Data

Out of the five data presentation examples, this is the simplest one.

Just write your findings coherently and your job is done. The demerit of this method is that one has to read the whole text to get a clear picture.  Yes, you read that right.

The introduction, summary, and conclusion can help condense the information.

2. Statistical data presentation

Data on its own is less valuable. However, for it to be valuable to your business, it has to be:

No matter how well manipulated, the insights into raw data should be presented in an easy-to-follow sequence to keep the audience waiting for more.

Text is the principal method for explaining findings, outlining trends, and providing contextual information. A table is best suited for representing individual information and represents both quantitative and qualitative information.

On the other hand, a graph is a very effective visual tool because:

  • It displays data at a glance
  • Facilitates comparison
  • Reveals trends, relationships, frequency distribution, and correlation

Text, tables, and graphs are incredibly effective data presentation examples you can leverage to curate persuasive data narratives.

3. Measure of Dispersion

Statistical dispersion is how a key metric is likely to deviate from the average value. In other words, dispersion can help you to understand the distribution of key data points.

There are two types of measures of dispersion, namely:

  • Absolute Measure of Dispersion
  • Relative Measure of Dispersion

4. Tabular Ways of Data Presentation and Analysis

To avoid the complexities associated with qualitative data, use tables and charts to display insights.

This is one of the data presentation examples where values are displayed in rows and columns. All rows and columns have an attribute (name, year, gender, and age).

5. Graphical Data Representation

Graphical representation uses charts and graphs to visually display, analyze, clarify, and interpret numerical data, functions, and other qualitative structures.

Data is ingested into charts and graphs, such as Sankey, and then represented by a variety of symbols, such as lines and bars.

Data presentation examples, such as Bar Charts , can help you illustrate trends, relationships, comparisons, and outliers between data points.

what are different types of data presentation

What is the main objective of data presentation?

Discovery and communication are the two key objectives of data presentation.

In the discovery phase, we recommend you try various charts and graphs to understand the insights into the raw data. The communication phase is focused on presenting the insights in a summarized form.

What is the importance of graphs and charts in business?

Big files with numbers are usually hard to read and make it difficult to spot patterns easily.

Presentation charts, maps, and graphs are vital because they simplify data by making it understandable & readable at the same time. Besides, they make data stories compelling and irresistible to target audiences.

Poring through numbers is tedious at best and mentally exhausting at worst.

This is where data presentation examples come into play.

Charts come in and distill data into meaningful insights. And this saves tons of hours, which you can use to handle other tasks. Besides, when creating data stories, it would be best if you had charts that communicate insights with clarity.

Excel, one of the popular tools for visualizing data, comes with very basic data presentation charts, which require a lot of editing.

We recommend you try ChartExpo because it’s one of the most trusted add-ins. Besides, it has a super-friendly user interface for everyone, irrespective of their computer skills.

Create simple, ready-made, and easy-to-interpret Bar Charts today without breaking a sweat.

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Data Presenting for Clearer Reference

Imagine the statistical data without a definite presentation, will be burdensome! Data presentation is one of the important aspects of Statistics. Presenting the data helps the users to study and explain the statistics thoroughly. We are going to discuss this presentation of data and know-how information is laid down methodically. 

In this context, we are going to present the topic - Presentation of Data which is to be referred to by the students and the same is to be studied in regard to the types of presentations of data. 

Presentation of Data and Information

Statistics is all about data. Presenting data effectively and efficiently is an art. You may have uncovered many truths that are complex and need long explanations while writing. This is where the importance of the presentation of data comes in. You have to present your findings in such a way that the readers can go through them quickly and understand each and every point that you wanted to showcase. As time progressed and new and complex research started happening, people realized the importance of the presentation of data to make sense of the findings.

Define Data Presentation

Data presentation is defined as the process of using various graphical formats to visually represent the relationship between two or more data sets so that an informed decision can be made based on them.

Types of Data Presentation

Broadly speaking, there are three methods of data presentation:

Diagrammatic

Textual Ways of Presenting Data

Out of the different methods of data presentation, this is the simplest one. You just write your findings in a coherent manner and your job is done. The demerit of this method is that one has to read the whole text to get a clear picture. Yes, the introduction, summary, and conclusion can help condense the information.

Tabular Ways of Data Presentation and Analysis

To avoid the complexities involved in the textual way of data presentation, people use tables and charts to present data. In this method, data is presented in rows and columns - just like you see in a cricket match showing who made how many runs. Each row and column have an attribute (name, year, sex, age, and other things like these). It is against these attributes that data is written within a cell.

Diagrammatic Presentation: Graphical Presentation of Data in Statistics

This kind of data presentation and analysis method says a lot with dramatically short amounts of time.

Diagrammatic Presentation has been divided into further categories:

Geometric Diagram

When a Diagrammatic presentation involves shapes like a bar or circle, we call that a Geometric Diagram. Examples of Geometric Diagram

Bar Diagram

Simple Bar Diagram

Simple Bar Diagram is composed of rectangular bars. All of these bars have the same width and are placed at an equal distance from each other. The bars are placed on the X-axis. The height or length of the bars is used as the means of measurement. So, on the Y-axis, you have the measurement relevant to the data. 

Suppose, you want to present the run scored by each batsman in a game in the form of a bar chart. Mark the runs on the Y-axis - in ascending order from the bottom. So, the lowest scorer will be represented in the form of the smallest bar and the highest scorer in the form of the longest bar.

Multiple Bar Diagram

(Image will be uploaded soon)

In many states of India, electric bills have bar diagrams showing the consumption in the last 5 months. Along with these bars, they also have bars that show the consumption that happened in the same months of the previous year. This kind of Bar Diagram is called Multiple Bar Diagrams.

Component Bar Diagram

(image will be uploaded soon)

Sometimes, a bar is divided into two or more parts. For example, if there is a Bar Diagram, the bars of which show the percentage of male voters who voted and who didn’t and the female voters who voted and who didn’t. Instead of creating separate bars for who did and who did not, you can divide one bar into who did and who did not.

A pie chart is a chart where you divide a pie (a circle) into different parts based on the data. Each of the data is first transformed into a percentage and then that percentage figure is multiplied by 3.6 degrees. The result that you get is the angular degree of that corresponding data to be drawn in the pie chart. So, for example, you get 30 degrees as the result, on the pie chart you draw that angle from the center.

Frequency Diagram

Suppose you want to present data that shows how many students have 1 to 2 pens, how many have 3 to 5 pens, how many have 6 to 10 pens (grouped frequency) you do that with the help of a Frequency Diagram. A Frequency Diagram can be of many kinds:

Where the grouped frequency of pens (from the above example) is written on the X-axis and the numbers of students are marked on the Y-axis. The data is presented in the form of bars.

Frequency Polygon

When you join the midpoints of the upper side of the rectangles in a histogram, you get a Frequency Polygon

Frequency Curve

When you draw a freehand line that passes through the points of the Frequency Polygon, you get a Frequency Curve.

Ogive 

Suppose 2 students got 0-20 marks in maths, 5 students got 20-30 marks and 4 students got 30-50 marks in Maths. So how many students got less than 50 marks? Yes, 5+2=7. And how many students got more than 20 marks? 5+4=9. This type of more than and less than data are represented in the form of the ogive. The meeting point of the less than and more than line will give you the Median.

Arithmetic Line Graph

If you want to see the trend of Corona infection vs the number of recoveries from January 2020 to December 2020, you can do that in the form of an Arithmetic Line Graph. The months should be marked on the X-axis and the number of infections and recoveries are marked on the Y-axis. You can compare if the recovery is greater than the infection and if the recovery and infection are going at the same rate or not with the help of this Diagram.

Did You Know?

Sir Ronald Aylmer Fisher is known as the father of modern statistics.

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FAQs on Presentation of Data

1. What are the 4 types of Tabular Presentation?

The tabular presentation method can be further divided into 4 categories:

Qualitative

Quantitative

Qualitative classification is done when the attributes in the table are some kind of ‘quality’ or feature. Suppose you want to make a table where you would show how many batsmen made half-centuries and how many batsmen made centuries in IPL 2020. Notice that the data would have only numbers - no age, sex, height is needed. This type of tabulation is called quantitative tabulation.

If you want to make a table that would inform which year’s world cup, which team won. The classifying variable, here, is year or time. This kind of classification is called Temporal classification.

If you want to list the top 5 coldest places in the world. The classifying variable here would be a place in each case. This kind of classification is called Spatial Classification.

2. Are bar charts and histograms the Same?

No, they are not the same. With a histogram, you measure the frequency of quantitative data. With bar charts, you compare categorical data.

3. What is the definition of Data Presentation?

When research work is completed, the data gathered from it can be quite large and complex. Organizing the data in a coherent, easy-to-understand, quick to read and graphical way is called data presentation.

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5 data presentation tips for communicating insights

  • Data Management

5 data presentation tips for communicating insights

Best data presentation tips.

  • Keep your audience in mind 
  • Focus on the big picture 
  • Use visuals to highlight main points
  • Think about how you’re presenting hard data
  • Choose the best type of chart for each main point

Collecting the right data and managing it correctly are essential to a successful business strategy. Data management helps you analyze raw data and glean insights to inform your next moves as a business. 

But you also need to be able to effectively communicate insights from that data. That’s where data presentation comes in. The future of your company is built on the data you collect in the present — and with proper data presentation, you can make sure the insights you’ve gained reach the stakeholders who matter.

The value of effective data presentation

Any business can collect data on its industry, customers, and performance — but successful businesses turn that raw data into action. Once you’ve gleaned insights from your data, it’s time to share them with decision makers and other stakeholders to convince them to pursue a course of action.

Rather than sharing random data points, you need to present information in a structured way that takes your audience on a journey to educate them on what you’ve found.

Spreadsheet after spreadsheet of data, no matter how solid and informative, can go to waste if you don’t present it in a way that’s easy for stakeholders to digest. In essence, data presentation is where the analytical and creative parts of data management meet.

5 tips for improving data presentation

Here are some quick and easy tips on how best to visualize and structure your data to make an impact and influence opinion.

1. Keep your audience in mind

Put yourself in your audience’s shoes before you set foot in the boardroom. Is the data you’ve collected easy to understand? Will it translate well from your laptop to a larger screen for you to present it? Are the colors and the formatting creating a pleasant visual experience?

Try a couple of practice runs of your presentation before you do the real thing. Ask a colleague who’s not connected to your upcoming meeting to observe you and offer feedback. You’re showcasing important data, and that should come across in the presentation.

2. Focus on the big picture

There’s a limit to the amount of information a person can absorb in one sitting. Don’t push your luck by overwhelming your audience with too many major data points and letting important takeaways slip through the cracks.

Instead, pick one major data point for each graph or visualization and stick to it. Stakeholders will more easily tie the insight you’re giving them to a graph or visualization if you don’t overload them.

Think back to some of your favorite classes as a student. Teachers often understand the value of tying important information to visuals — it can help students remember what they’ve learned . You’re the teacher in this scenario, so the same principle applies.

3. Use visuals to highlight main points

To that end, you can create visual highlights that draw attention to a particular number or data range you need your audience to understand. There are several ways to do this.

You can literally highlight that information in a graph or chart, or you can craft a specific slide around it. Just make sure there are clear visuals tied to the “aha” moment you want to communicate.

To bring the point home, take a moment to explain why this data is important. Accompany this pause with bullet points stating the same information for greater effect.

4. Think about how you’re presenting hard data

If your job involves a lot of data management, odds are you’re comfortable with numbers. Unfortunately, not everyone feels the same way. For some, seeing a lot of figures and percentages can be more confusing than illuminating, so do your best to reduce the anxiety some people feel when faced with big or complicated numbers.

Try these tips:

  • Don’t make your audience count zeroes (“10,000” instead of “10000”).
  • Avoid decimals if possible (“5” instead of “5.02”).
  • Align important data on the right side of a chart, allowing your audience to quickly compare values.

5. Choose the best type of chart for each main point

Charts and graphs are useful when you’re showing and comparing data, so they’re an essential part of data presentation. But your audience is likely already familiar with different types of charts (and their intended purposes), so picking the wrong one is a fast way to lose credibility during a presentation. Here’s a quick reference to help you choose the right chart for different data:

  • Line graph: These graphs are great for depicting trends and plotting specific data points along a trend line.
  • Bar chart: These charts are best used when making comparisons between data points.
  • Pie chart: Pie charts show percentages of a whole — for example, the percentages of respondents who chose each answer option in a survey.
  • Scatter plot: These charts place different variables on an X/Y axis to investigate the relationship between one variable and another. If you want to show which variable has the greatest impact in a given situation, a scatter plot can help.

Tools for enhancing data presentation

Once you’ve got a good idea of how you’d like to present your data, you can reduce some of the legwork in crafting a great presentation by automating the visualization processes. With Jotform’s report building tool, you can generate dynamic visual reports based on the data you provide and the customization options you select.

The more you work on data management, the better the data you collect can work for you. Harnessing the power of numbers is vital to implementing the next strategy that will define your business, and effective data presentation will ensure your organization’s stats get the attention they deserve.

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Presentation of Data

Statistics deals with the collection, presentation and analysis of the data, as well as drawing meaningful conclusions from the given data. Generally, the data can be classified into two different types, namely primary data and secondary data. If the information is collected by the investigator with a definite objective in their mind, then the data obtained is called the primary data. If the information is gathered from a source, which already had the information stored, then the data obtained is called secondary data. Once the data is collected, the presentation of data plays a major role in concluding the result. Here, we will discuss how to present the data with many solved examples.

What is Meant by Presentation of Data?

As soon as the data collection is over, the investigator needs to find a way of presenting the data in a meaningful, efficient and easily understood way to identify the main features of the data at a glance using a suitable presentation method. Generally, the data in the statistics can be presented in three different forms, such as textual method, tabular method and graphical method.

Presentation of Data Examples

Now, let us discuss how to present the data in a meaningful way with the help of examples.

Consider the marks given below, which are obtained by 10 students in Mathematics:

36, 55, 73, 95, 42, 60, 78, 25, 62, 75.

Find the range for the given data.

Given Data: 36, 55, 73, 95, 42, 60, 78, 25, 62, 75.

The data given is called the raw data.

First, arrange the data in the ascending order : 25, 36, 42, 55, 60, 62, 73, 75, 78, 95.

Therefore, the lowest mark is 25 and the highest mark is 95.

We know that the range of the data is the difference between the highest and the lowest value in the dataset.

Therefore, Range = 95-25 = 70.

Note: Presentation of data in ascending or descending order can be time-consuming if we have a larger number of observations in an experiment.

Now, let us discuss how to present the data if we have a comparatively more number of observations in an experiment.

Consider the marks obtained by 30 students in Mathematics subject (out of 100 marks)

10, 20, 36, 92, 95, 40, 50, 56, 60, 70, 92, 88, 80, 70, 72, 70, 36, 40, 36, 40, 92, 40, 50, 50, 56, 60, 70, 60, 60, 88.

In this example, the number of observations is larger compared to example 1. So, the presentation of data in ascending or descending order is a bit time-consuming. Hence, we can go for the method called ungrouped frequency distribution table or simply frequency distribution table . In this method, we can arrange the data in tabular form in terms of frequency.

For example, 3 students scored 50 marks. Hence, the frequency of 50 marks is 3. Now, let us construct the frequency distribution table for the given data.

Therefore, the presentation of data is given as below:

The following example shows the presentation of data for the larger number of observations in an experiment.

Consider the marks obtained by 100 students in a Mathematics subject (out of 100 marks)

95, 67, 28, 32, 65, 65, 69, 33, 98, 96,76, 42, 32, 38, 42, 40, 40, 69, 95, 92, 75, 83, 76, 83, 85, 62, 37, 65, 63, 42, 89, 65, 73, 81, 49, 52, 64, 76, 83, 92, 93, 68, 52, 79, 81, 83, 59, 82, 75, 82, 86, 90, 44, 62, 31, 36, 38, 42, 39, 83, 87, 56, 58, 23, 35, 76, 83, 85, 30, 68, 69, 83, 86, 43, 45, 39, 83, 75, 66, 83, 92, 75, 89, 66, 91, 27, 88, 89, 93, 42, 53, 69, 90, 55, 66, 49, 52, 83, 34, 36.

Now, we have 100 observations to present the data. In this case, we have more data when compared to example 1 and example 2. So, these data can be arranged in the tabular form called the grouped frequency table. Hence, we group the given data like 20-29, 30-39, 40-49, ….,90-99 (As our data is from 23 to 98). The grouping of data is called the “class interval” or “classes”, and the size of the class is called “class-size” or “class-width”.

In this case, the class size is 10. In each class, we have a lower-class limit and an upper-class limit. For example, if the class interval is 30-39, the lower-class limit is 30, and the upper-class limit is 39. Therefore, the least number in the class interval is called the lower-class limit and the greatest limit in the class interval is called upper-class limit.

Hence, the presentation of data in the grouped frequency table is given below:

Hence, the presentation of data in this form simplifies the data and it helps to enable the observer to understand the main feature of data at a glance.

Practice Problems

  • The heights of 50 students (in cms) are given below. Present the data using the grouped frequency table by taking the class intervals as 160 -165, 165 -170, and so on.  Data: 161, 150, 154, 165, 168, 161, 154, 162, 150, 151, 162, 164, 171, 165, 158, 154, 156, 172, 160, 170, 153, 159, 161, 170, 162, 165, 166, 168, 165, 164, 154, 152, 153, 156, 158, 162, 160, 161, 173, 166, 161, 159, 162, 167, 168, 159, 158, 153, 154, 159.
  • Three coins are tossed simultaneously and each time the number of heads occurring is noted and it is given below. Present the data using the frequency distribution table. Data: 0, 1, 2, 2, 1, 2, 3, 1, 3, 0, 1, 3, 1, 1, 2, 2, 0, 1, 2, 1, 3, 0, 0, 1, 1, 2, 3, 2, 2, 0.

To learn more Maths-related concepts, stay tuned with BYJU’S – The Learning App and download the app today!

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8 Types of Presentations You Should Know [+Examples & Tips]

By Krystle Wong , Aug 11, 2023

Types of Presentation

From persuasive pitches that influence opinions to instructional demonstrations that teach skills, the different types of presentations serve a unique purpose, tailored to specific objectives and audiences.

Presentations that are tailored to its objectives and audiences are more engaging and memorable. They capture attention, maintain interest and leave a lasting impression. 

Don’t worry if you’re no designer —  Whether you need data-driven visuals, persuasive graphics or engaging design elements, Venngage can empower you to craft presentations that stand out and effectively convey your message.

Venngage’s intuitive drag-and-drop interface, extensive presentation template library and customizable design options make it a valuable tool for creating slides that align with your specific goals and target audience. 

Click to jump ahead:

8 Different types of presentations every presenter must know

How do i choose the right type of presentation for my topic or audience, types of presentation faq, 5 steps to create a presentation with venngage .

what are different types of data presentation

When it comes to presentations, versatility is the name of the game. Having a variety of presentation styles up your sleeve can make a world of difference in keeping your audience engaged. Here are 8 essential presentation types that every presenter should be well-acquainted with:

1. Informative presentation

Ever sat through a presentation that left you feeling enlightened? That’s the power of an informative presentation. 

This presentation style is all about sharing knowledge and shedding light on a particular topic. Whether you’re diving into the depths of quantum physics or explaining the intricacies of the latest social media trends, informative presentations aim to increase the audience’s understanding.

When delivering an informative presentation, simplify complex topics with clear visuals and relatable examples. Organize your content logically, starting with the basics and gradually delving deeper and always remember to keep jargon to a minimum and encourage questions for clarity.

Academic presentations and research presentations are great examples of informative presentations. An effective academic presentation involves having clear structure, credible evidence, engaging delivery and supporting visuals. Provide context to emphasize the topic’s significance, practice to perfect timing, and be ready to address anticipated questions. 

what are different types of data presentation

2. Persuasive presentation

If you’ve ever been swayed by a passionate speaker armed with compelling arguments, you’ve experienced a persuasive presentation . 

This type of presentation is like a verbal tug-of-war, aiming to convince the audience to see things from a specific perspective. Expect to encounter solid evidence, logical reasoning and a dash of emotional appeal.

With persuasive presentations, it’s important to know your audience inside out and tailor your message to their interests and concerns. Craft a compelling narrative with a strong opening, a solid argument and a memorable closing. Additionally, use visuals strategically to enhance your points.

Examples of persuasive presentations include presentations for environmental conservations, policy change, social issues and more. Here are some engaging presentation templates you can use to get started with: 

what are different types of data presentation

3. Demonstration or how-to presentation

A Demonstration or How-To Presentation is a type of presentation where the speaker showcases a process, technique, or procedure step by step, providing the audience with clear instructions on how to replicate the demonstrated action. 

A demonstrative presentation is particularly useful when teaching practical skills or showing how something is done in a hands-on manner.

These presentations are commonly used in various settings, including educational workshops, training sessions, cooking classes, DIY tutorials, technology demonstrations and more. Designing creative slides for your how-to presentations can heighten engagement and foster better information retention. 

Speakers can also consider breaking down the process into manageable steps, using visual aids, props and sometimes even live demonstrations to illustrate each step. The key is to provide clear and concise instructions, engage the audience with interactive elements and address any questions that may arise during the presentation.

what are different types of data presentation

4. Training or instructional presentation

Training presentations are geared towards imparting practical skills, procedures or concepts — think of this as the more focused cousin of the demonstration presentation. 

Whether you’re teaching a group of new employees the ins and outs of a software or enlightening budding chefs on the art of soufflé-making, training presentations are all about turning novices into experts.

To maximize the impact of your training or instructional presentation, break down complex concepts into digestible segments. Consider using real-life examples to illustrate each point and create a connection. 

You can also create an interactive presentation by incorporating elements like quizzes or group activities to reinforce understanding.

what are different types of data presentation

5. Sales presentation

Sales presentations are one of the many types of business presentations and the bread and butter of businesses looking to woo potential clients or customers. With a sprinkle of charm and a dash of persuasion, these presentations showcase products, services or ideas with one end goal in mind: sealing the deal.

A successful sales presentation often has key characteristics such as a clear value proposition, strong storytelling, confidence and a compelling call to action. Hence, when presenting to your clients or stakeholders, focus on benefits rather than just features. 

Anticipate and address potential objections before they arise and use storytelling to showcase how your offering solves a specific problem for your audience. Utilizing visual aids is also a great way to make your points stand out and stay memorable.

A sales presentation can be used to promote service offerings, product launches or even consultancy proposals that outline the expertise and industry experience of a business. Here are some template examples you can use for your next sales presentation:

what are different types of data presentation

6. Pitch presentation

Pitch presentations are your ticket to garnering the interest and support of potential investors, partners or stakeholders. Think of your pitch deck as your chance to paint a vivid picture of your business idea or proposal and secure the resources you need to bring it to life. 

Business presentations aside, individuals can also create a portfolio presentation to showcase their skills, experience and achievements to potential clients, employers or investors. 

Craft a concise and compelling narrative. Clearly define the problem your idea solves and how it stands out in the market. Anticipate questions and practice your answers. Project confidence and passion for your idea.

what are different types of data presentation

7. Motivational or inspirational presentation

Feeling the need for a morale boost? That’s where motivational presentations step in. These talks are designed to uplift and inspire, often featuring personal anecdotes, heartwarming stories and a generous serving of encouragement.

Form a connection with your audience by sharing personal stories that resonate with your message. Use a storytelling style with relatable anecdotes and powerful metaphors to create an emotional connection. Keep the energy high and wrap up your inspirational presentations with a clear call to action.

Inspirational talks and leadership presentations aside, a motivational or inspirational presentation can also be a simple presentation aimed at boosting confidence, a motivational speech focused on embracing change and more.

what are different types of data presentation

8. Status or progress report presentation

Projects and businesses are like living organisms, constantly evolving and changing. Status or progress report presentations keep everyone in the loop by providing updates on achievements, challenges and future plans. It’s like a GPS for your team, ensuring everyone stays on track.

Be transparent about achievements, challenges and future plans. Utilize infographics, charts and diagrams to present your data visually and simplify information. By visually representing data, it becomes easier to identify trends, make predictions and strategize based on evidence.

what are different types of data presentation

Now that you’ve learned about the different types of presentation methods and how to use them, you’re on the right track to creating a good presentation that can boost your confidence and enhance your presentation skills . 

Selecting the most suitable presentation style is akin to choosing the right outfit for an occasion – it greatly influences how your message is perceived. Here’s a more detailed guide to help you make that crucial decision:

1. Define your objectives

Begin by clarifying your presentation’s goals. Are you aiming to educate, persuade, motivate, train or perhaps sell a concept? Your objectives will guide you to the most suitable presentation type. 

For instance, if you’re aiming to inform, an informative presentation would be a natural fit. On the other hand, a persuasive presentation suits the goal of swaying opinions.

2. Know your audience

Regardless if you’re giving an in-person or a virtual presentation — delve into the characteristics of your audience. Consider factors like their expertise level, familiarity with the topic, interests and expectations. 

If your audience consists of professionals in your field, a more technical presentation might be suitable. However, if your audience is diverse and includes newcomers, an approachable and engaging style might work better.

what are different types of data presentation

3. Analyze your content

Reflect on the content you intend to present. Is it data-heavy, rich in personal stories or focused on practical skills? Different presentation styles serve different content types. 

For data-driven content, an informative or instructional presentation might work best. For emotional stories, a motivational presentation could be a compelling choice.

4. Consider time constraints

Evaluate the time you have at your disposal. If your presentation needs to be concise due to time limitations, opt for a presentation style that allows you to convey your key points effectively within the available timeframe. A pitch presentation, for example, often requires delivering impactful information within a short span.

5. Leverage visuals

Visual aids are powerful tools in presentations. Consider whether your content would benefit from visual representation. If your PowerPoint presentations involve step-by-step instructions or demonstrations, a how-to presentation with clear visuals would be advantageous. Conversely, if your content is more conceptual, a motivational presentation could rely more on spoken words.

what are different types of data presentation

6. Align with the setting

Take the presentation environment into account. Are you presenting in a formal business setting, a casual workshop or a conference? Your setting can influence the level of formality and interactivity in your presentation. For instance, a demonstration presentation might be ideal for a hands-on workshop, while a persuasive presentation is great for conferences.

7. Gauge audience interaction

Determine the level of audience engagement you want. Interactive presentations work well for training sessions, workshops and small group settings, while informative or persuasive presentations might be more one-sided.

8. Flexibility

Stay open to adjusting your presentation style on the fly. Sometimes, unexpected factors might require a change of presentation style. Be prepared to adjust on the spot if audience engagement or reactions indicate that a different approach would be more effective.

Remember that there is no one-size-fits-all approach, and the best type of presentation may vary depending on the specific situation and your unique communication goals. By carefully considering these factors, you can choose the most effective presentation type to successfully engage and communicate with your audience.

To save time, use a presentation software or check out these presentation design and presentation background guides to create a presentation that stands out.    

what are different types of data presentation

What are some effective ways to begin and end a presentation?

Capture your audience’s attention from the start of your presentation by using a surprising statistic, a compelling story or a thought-provoking question related to your topic. 

To conclude your presentation , summarize your main points, reinforce your key message and leave a lasting impression with a powerful call to action or a memorable quote that resonates with your presentation’s theme.

How can I make my presentation more engaging and interactive?

To create an engaging and interactive presentation for your audience, incorporate visual elements such as images, graphs and videos to illustrate your points visually. Share relatable anecdotes or real-life examples to create a connection with your audience. 

You can also integrate interactive elements like live polls, open-ended questions or small group discussions to encourage participation and keep your audience actively engaged throughout your presentation.

Which types of presentations require special markings

Some presentation types require special markings such as how sales presentations require persuasive techniques like emphasizing benefits, addressing objections and using compelling visuals to showcase products or services. 

Demonstrations and how-to presentations on the other hand require clear markings for each step, ensuring the audience can follow along seamlessly. 

That aside, pitch presentations require highlighting unique selling points, market potential and the competitive edge of your idea, making it stand out to potential investors or partners.

Need some inspiration on how to make a presentation that will captivate an audience? Here are 120+ presentation ideas to help you get started. 

Creating a stunning and impactful presentation with Venngage is a breeze. Whether you’re crafting a business pitch, a training presentation or any other type of presentation, follow these five steps to create a professional presentation that stands out:

  • Sign up and log in to Venngage to access the editor.
  • Choose a presentation template that matches your topic or style.
  • Customize content, colors, fonts, and background to personalize your presentation.
  • Add images, icons, and charts to enhancevisual style and clarity.
  • Save, export, and share your presentation as PDF or PNG files, or use Venngage’s Presentation Mode for online showcasing.

In the realm of presentations, understanding the different types of presentation formats is like having a versatile set of tools that empower you to craft compelling narratives for every occasion.

Remember, the key to a successful presentation lies not only in the content you deliver but also in the way you connect with your audience. Whether you’re informing, persuading or entertaining, tailoring your approach to the specific type of presentation you’re delivering can make all the difference.

Presentations are a powerful tool, and with practice and dedication (and a little help from Venngage), you’ll find yourself becoming a presentation pro in no time. Now, let’s get started and customize your next presentation!

EU AI Act: first regulation on artificial intelligence

The use of artificial intelligence in the EU will be regulated by the AI Act, the world’s first comprehensive AI law. Find out how it will protect you.

A man faces a computer generated figure with programming language in the background

As part of its digital strategy , the EU wants to regulate artificial intelligence (AI) to ensure better conditions for the development and use of this innovative technology. AI can create many benefits , such as better healthcare; safer and cleaner transport; more efficient manufacturing; and cheaper and more sustainable energy.

In April 2021, the European Commission proposed the first EU regulatory framework for AI. It says that AI systems that can be used in different applications are analysed and classified according to the risk they pose to users. The different risk levels will mean more or less regulation. Once approved, these will be the world’s first rules on AI.

Learn more about what artificial intelligence is and how it is used

What Parliament wants in AI legislation

Parliament’s priority is to make sure that AI systems used in the EU are safe, transparent, traceable, non-discriminatory and environmentally friendly. AI systems should be overseen by people, rather than by automation, to prevent harmful outcomes.

Parliament also wants to establish a technology-neutral, uniform definition for AI that could be applied to future AI systems.

Learn more about Parliament’s work on AI and its vision for AI’s future

AI Act: different rules for different risk levels

The new rules establish obligations for providers and users depending on the level of risk from artificial intelligence. While many AI systems pose minimal risk, they need to be assessed.

Unacceptable risk

Unacceptable risk AI systems are systems considered a threat to people and will be banned. They include:

  • Cognitive behavioural manipulation of people or specific vulnerable groups: for example voice-activated toys that encourage dangerous behaviour in children
  • Social scoring: classifying people based on behaviour, socio-economic status or personal characteristics
  • Biometric identification and categorisation of people
  • Real-time and remote biometric identification systems, such as facial recognition

Some exceptions may be allowed for law enforcement purposes. “Real-time” remote biometric identification systems will be allowed in a limited number of serious cases, while “post” remote biometric identification systems, where identification occurs after a significant delay, will be allowed to prosecute serious crimes and only after court approval.

AI systems that negatively affect safety or fundamental rights will be considered high risk and will be divided into two categories:

1) AI systems that are used in products falling under the EU’s product safety legislation . This includes toys, aviation, cars, medical devices and lifts.

2) AI systems falling into specific areas that will have to be registered in an EU database:

  • Management and operation of critical infrastructure
  • Education and vocational training
  • Employment, worker management and access to self-employment
  • Access to and enjoyment of essential private services and public services and benefits
  • Law enforcement
  • Migration, asylum and border control management
  • Assistance in legal interpretation and application of the law.

All high-risk AI systems will be assessed before being put on the market and also throughout their lifecycle.

General purpose and generative AI

Generative AI, like ChatGPT, would have to comply with transparency requirements:

  • Disclosing that the content was generated by AI
  • Designing the model to prevent it from generating illegal content
  • Publishing summaries of copyrighted data used for training

High-impact general-purpose AI models that might pose systemic risk, such as the more advanced AI model GPT-4, would have to undergo thorough evaluations and any serious incidents would have to be reported to the European Commission.

Limited risk

Limited risk AI systems should comply with minimal transparency requirements that would allow users to make informed decisions. After interacting with the applications, the user can then decide whether they want to continue using it. Users should be made aware when they are interacting with AI. This includes AI systems that generate or manipulate image, audio or video content, for example deepfakes.

On December 9 2023, Parliament reached a provisional agreement with the Council on the AI act . The agreed text will now have to be formally adopted by both Parliament and Council to become EU law. Before all MEPs have their say on the agreement, Parliament’s internal market and civil liberties committees will vote on it.

More on the EU’s digital measures

  • Cryptocurrency dangers and the benefits of EU legislation
  • Fighting cybercrime: new EU cybersecurity laws explained
  • Boosting data sharing in the EU: what are the benefits?
  • EU Digital Markets Act and Digital Services Act
  • Five ways the European Parliament wants to protect online gamers
  • Artificial Intelligence Act

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  1. Data Presentation

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    1. Bar graph Ideal for comparing data across categories or showing trends over time. Bar graphs, also known as bar charts are workhorses of data presentation. They're like the Swiss Army knives of visualization methods because they can be used to compare data in different categories or display data changes over time.

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    9 mins read Share this article Presenting data in PowerPoint is easy. But presenting data in PowerPoint in visual and effective ways take a lot more time and effort. It's not hard to bore your audience with the same old formats of data presentation. So there is basically one simple golden rule. Make it not boring.

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