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Effective Tips and Tricks for Studying

No matter how old you are, there’s always room for improvement when it comes to studying. Whether you’re taking the biggest exam of your life or you know your teacher or professor is going to give a pop quiz soon, efficient studying is a great way to be prepared.

Create a Routine

One of the best things you can do for yourself, whether you’re in fifth grade or college, is to make studying a habit. One helpful way to do that is to find a way to incorporate it into your daily routine at the same time every day. Perhaps it’s after dinner or right when you get home from school. Find the time that works for you, and make yourself sit down to study and handle any homework you have at that time every day or on as many days as possible.

Break It Up

Everyone’s been there. You wait until the very last minute to study, and you do it all in one sitting. Not only is it exhausting, but you probably also don’t even remember half of what you study. This is why it can be better to break it up and do a little bit each day. If you have a big project coming up in a few weeks, break it down into steps, and take on one of the steps every other day until everything is complete. If you have plenty of reading to do, break it down into chapters or pages, and read one section each day.

Get Some Sleep

While it can be tempting to stay up all night studying before a big exam, you’re better off getting sleep. Your brain and memory function better when you’re rested, so you can retain more of the information and do better on your test. If you didn’t get a full night of sleep, consider napping briefly during the day to help catch yourself up on sleep.

Clear Your Mind

Before you sit down to study, make sure you have a clear mind and that you’re not focused on something else. Take a walk, listen to some music, read a book or do some stretches. Try meditation. Do whatever it takes to get your mind in the right mood for study time. Be sure to take breaks while you study too. Resting for five minutes every 30 to 60 minutes may help you retain the information.

Create the Right Environment

Finally, create a good study environment. It can be hard to pay attention when the TV is on or when you’re constantly receiving texts from friends. Turn off your devices. If you don’t do well with quiet, use a fan for background noise, or turn on a radio. You may find it more effective to study to music that doesn’t have lyrics. Make sure you’re comfortable and organized. You’ll also want to make sure you have plenty of water and a few healthy snacks on hand if you’ll be studying for a while.


examples of study variables

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Types of Variables in Research & Statistics | Examples

Published on September 19, 2022 by Rebecca Bevans . Revised on December 2, 2022.

In statistical research , a variable is defined as an attribute of an object of study. Choosing which variables to measure is central to good experimental design .

If you want to test whether some plant species are more salt-tolerant than others, some key variables you might measure include the amount of salt you add to the water, the species of plants being studied, and variables related to plant health like growth and wilting .

You need to know which types of variables you are working with in order to choose appropriate statistical tests and interpret the results of your study.

You can usually identify the type of variable by asking two questions:

Table of contents

Types of data: quantitative vs categorical variables, parts of the experiment: independent vs dependent variables, other common types of variables, frequently asked questions about variables.

Data is a specific measurement of a variable – it is the value you record in your data sheet. Data is generally divided into two categories:

A variable that contains quantitative data is a quantitative variable ; a variable that contains categorical data is a categorical variable . Each of these types of variables can be broken down into further types.

Quantitative variables

When you collect quantitative data, the numbers you record represent real amounts that can be added, subtracted, divided, etc. There are two types of quantitative variables: discrete and continuous .

Categorical variables

Categorical variables represent groupings of some kind. They are sometimes recorded as numbers, but the numbers represent categories rather than actual amounts of things.

There are three types of categorical variables: binary , nominal , and ordinal variables .

*Note that sometimes a variable can work as more than one type! An ordinal variable can also be used as a quantitative variable if the scale is numeric and doesn’t need to be kept as discrete integers. For example, star ratings on product reviews are ordinal (1 to 5 stars), but the average star rating is quantitative.

Example data sheet

To keep track of your salt-tolerance experiment, you make a data sheet where you record information about the variables in the experiment, like salt addition and plant health.

To gather information about plant responses over time, you can fill out the same data sheet every few days until the end of the experiment. This example sheet is color-coded according to the type of variable: nominal , continuous , ordinal , and binary .

Example data sheet showing types of variables in a plant salt tolerance experiment

Experiments are usually designed to find out what effect one variable has on another – in our example, the effect of salt addition on plant growth.

You manipulate the independent variable (the one you think might be the cause ) and then measure the dependent variable (the one you think might be the effect ) to find out what this effect might be.

You will probably also have variables that you hold constant ( control variables ) in order to focus on your experimental treatment.

In this experiment, we have one independent and three dependent variables.

The other variables in the sheet can’t be classified as independent or dependent, but they do contain data that you will need in order to interpret your dependent and independent variables.

Example of a data sheet showing dependent and independent variables for a plant salt tolerance experiment.

What about correlational research?

When you do correlational research , the terms “dependent” and “independent” don’t apply, because you are not trying to establish a cause and effect relationship ( causation ).

However, there might be cases where one variable clearly precedes the other (for example, rainfall leads to mud, rather than the other way around). In these cases you may call the preceding variable (i.e., the rainfall) the predictor variable and the following variable (i.e. the mud) the outcome variable .

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examples of study variables

Once you have defined your independent and dependent variables and determined whether they are categorical or quantitative, you will be able to choose the correct statistical test .

But there are many other ways of describing variables that help with interpreting your results. Some useful types of variables are listed below.

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

Discrete and continuous variables are two types of quantitative variables :

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Table of Contents

Definition of Variable

The next section provides examples of variables related to climate change , academic performance, crime, fish kill, crop growth, and how content goes viral. Note that the variables in these phenomena can be measured, except the last one, where a bit more work is required.

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Examples of Variables in Research: 6 Phenomena

Phenomenon 1: climate change, phenomenon 2: crime and violence in the streets, phenomenon 3: poor performance of students in college entrance exams, phenomenon 4: fish kill, phenomenon 5: poor crop growth, phenomenon 6:  how content goes viral.

The expected values derived from these variables will be in terms of numbers, amount, category, or type. Quantified variables allow statistical analysis . Variable descriptions, correlations, or differences are then determined.

Difference Between Independent and Dependent Variables

Independent variables, dependent variables, finding the relationship between variables, related posts, alvior’s theory of learning in higher education, four statistical scales of measurement, 10 tips to generate your research topic, about the author, regoniel, patrick, 132 comments, leave a reply cancel reply.

Types of Research Variable in Research with Example

What is the research variable and what are its types?

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The terms variable and constant refer to changes of statistical patterns of random or real data that can lead to some changes in the resulting state of the system.

In other words, variables are any characteristics that can take on different values namely age, test marks, temperature, pressure, weight, etc.

Dependent and independent variables are measured during experimental studies to assess the cause-and-effect relationship.

What is a Dependent Variable in Research?

A dependent variable is a variable that varies with respect to change in the independent variable. The value of the dependent variable depends on the value of an independent variable. In statistics, dependent variables can be categorized into:

The dependent variable is what we measure after varying the independent variable from low to high. This measurement is done to study the effect of the dependent variable on the independent variable by conducting statistical analyses. Based on the results, the degree to which the independent variable variation can be studied.

What is an Independent Variable?

An independent variable is a variable that we vary in an experimental study to measure its effects. It is called “independent” as it is not affected by any other variables in the study. Independent variables can be categorized into:

These terminologies are used in statistics, where we can study the degree to which an independent variable change can predict changes in the dependent variable.

Types of independent variables

There are two main types of independent variables.

The Independent variable is the cause. Its value is independent of other variables. The dependent variable is the effect. Its value is based on the changes in the independent variable. ilovephd .com

Example : Independent and dependent variables

You conduct a study to assess whether changes in pressure affect the reactor performance.

Your independent variable is the pressure of the reactor. You can vary the pressure by making it low for 30 minutes and high for another 30 minutes.

Your dependent variable is the performance of the reactor. Now, calculate the performance of the reactor and analyze the change in pressure have an effect on reactor performance.

How to Find Dependent and Independent Variables in Research?

Ascertaining dependent and independent variables can be difficult or tricky while designing research experiments. A dependent variable in one research study can be the independent variable in another study; therefore it’s important to identify the variables while formulating the design of experiments.

Tips to identify dependent variable type:

The following research questions can be used to identify the dependent variable:

Tips to identify independent variable type:

The following research questions can be used to identify the independent variable:

Dependent and independent variables are used in the experimental and quasi-experimental research study. Some of the research questions and their dependent and independent variables are listed.

The results can be analyzed by generating descriptive statistics and an appropriate statistical test method can be used to test the research hypothesis. The type of test method depends on the type of variable, level of measurement, and number of independent variables. Most often, t-tests or ANOVA tests are used to assess the experimental data.

We hope that this article helps you to understand what is research variable and how to identify research variable types for designing experiments.

Also Read: Quantitative Vs Qualitative Research

How to Write a Research Paper? Research Paper Format

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Organizing Your Social Sciences Research Paper


Dependent Variable The variable that depends on other factors that are measured. These variables are expected to change as a result of an experimental manipulation of the independent variable or variables. It is the presumed effect.

Independent Variable The variable that is stable and unaffected by the other variables you are trying to measure. It refers to the condition of an experiment that is systematically manipulated by the investigator. It is the presumed cause.

Cramer, Duncan and Dennis Howitt. The SAGE Dictionary of Statistics . London: SAGE, 2004; Penslar, Robin Levin and Joan P. Porter. Institutional Review Board Guidebook: Introduction . Washington, DC: United States Department of Health and Human Services, 2010; "What are Dependent and Independent Variables?" Graphic Tutorial.

Identifying Dependent and Independent Variables

Don't feel bad if you are confused about what is the dependent variable and what is the independent variable in social and behavioral sciences research . However, it's important that you learn the difference because framing a study using these variables is a common approach to organizing the elements of a social sciences research study in order to discover relevant and meaningful results. Specifically, it is important for these two reasons:

A variable in research simply refers to a person, place, thing, or phenomenon that you are trying to measure in some way. The best way to understand the difference between a dependent and independent variable is that the meaning of each is implied by what the words tell us about the variable you are using. You can do this with a simple exercise from the website, Graphic Tutorial. Take the sentence, "The [independent variable] causes a change in [dependent variable] and it is not possible that [dependent variable] could cause a change in [independent variable]." Insert the names of variables you are using in the sentence in the way that makes the most sense. This will help you identify each type of variable. If you're still not sure, consult with your professor before you begin to write.

Fan, Shihe. "Independent Variable." In Encyclopedia of Research Design. Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 592-594; "What are Dependent and Independent Variables?" Graphic Tutorial; Salkind, Neil J. "Dependent Variable." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 348-349;

Structure and Writing Style

The process of examining a research problem in the social and behavioral sciences is often framed around methods of analysis that compare, contrast, correlate, average, or integrate relationships between or among variables . Techniques include associations, sampling, random selection, and blind selection. Designation of the dependent and independent variable involves unpacking the research problem in a way that identifies a general cause and effect and classifying these variables as either independent or dependent.

The variables should be outlined in the introduction of your paper and explained in more detail in the methods section . There are no rules about the structure and style for writing about independent or dependent variables but, as with any academic writing, clarity and being succinct is most important.

After you have described the research problem and its significance in relation to prior research, explain why you have chosen to examine the problem using a method of analysis that investigates the relationships between or among independent and dependent variables . State what it is about the research problem that lends itself to this type of analysis. For example, if you are investigating the relationship between corporate environmental sustainability efforts [the independent variable] and dependent variables associated with measuring employee satisfaction at work using a survey instrument, you would first identify each variable and then provide background information about the variables. What is meant by "environmental sustainability"? Are you looking at a particular company [e.g., General Motors] or are you investigating an industry [e.g., the meat packing industry]? Why is employee satisfaction in the workplace important? How does a company make their employees aware of sustainability efforts and why would a company even care that its employees know about these efforts?

Identify each variable for the reader and define each . In the introduction, this information can be presented in a paragraph or two when you describe how you are going to study the research problem. In the methods section, you build on the literature review of prior studies about the research problem to describe in detail background about each variable, breaking each down for measurement and analysis. For example, what activities do you examine that reflect a company's commitment to environmental sustainability? Levels of employee satisfaction can be measured by a survey that asks about things like volunteerism or a desire to stay at the company for a long time.

The structure and writing style of describing the variables and their application to analyzing the research problem should be stated and unpacked in such a way that the reader obtains a clear understanding of the relationships between the variables and why they are important. This is also important so that the study can be replicated in the future using the same variables but applied in a different way.

Fan, Shihe. "Independent Variable." In Encyclopedia of Research Design. Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 592-594; "What are Dependent and Independent Variables?" Graphic Tutorial; “Case Example for Independent and Dependent Variables.” ORI Curriculum Examples. U.S. Department of Health and Human Services, Office of Research Integrity; Salkind, Neil J. "Dependent Variable." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 348-349; “Independent Variables and Dependent Variables.” Karl L. Wuensch, Department of Psychology, East Carolina University [posted email exchange]; “Variables.” Elements of Research. Dr. Camille Nebeker, San Diego State University.

Independent and Dependent Variables: Definitions & Examples

Saul Mcleod, PhD

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BSc (Hons) Psychology, MRes, PhD, University of Manchester

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BSc (Hons), Psychology, MSc, Psychology of Education

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Variables are given a special name that only applies to experimental investigations . One is called the dependent variable, and the other is the independent variable.

examples of study variables

Independent Variable

The independent variable is the variable the experimenter manipulates or changes and is assumed to directly affect the dependent variable.

For example, allocating participants to drug or placebo conditions (independent variable) to measure any changes in the intensity of their anxiety (dependent variable).

In a well-designed experimental study , the independent variable is the only important difference between the experimental (e.g., treatment) and control (e.g., placebo) groups.

Dependent Variable

The dependent variable is the variable being tested and measured in an experiment and is “dependent” on the independent variable.

An example of a dependent variable is depression symptoms, which depend on the independent variable (type of therapy).

In an experiment, the researcher looks for the possible effect on the dependent variable that might be caused by changing the independent variable.

Examples in Experiments

For example, we might change the type of information (e.g., organized or random) given to participants to see what effect this might have on the amount of information remembered.

In this particular example, the type of information is the independent variable (because it changes), and the amount of information remembered is the dependent variable (because this is being measured).

Independent and Dependent Variables Examples

For the following hypotheses, name the IV and the DV.

1. Lack of sleep significantly affects learning in 10-year-old boys.



2. Social class has a significant effect on IQ scores.


3. Stressful experiences significantly increase the likelihood of headaches.

4. Time of day has a significant effect on alertness.

Operationalizing Variables

To ensure cause and effect are established, it is important that we identify exactly how the independent and dependent variables will be measured; this is known as operationalizing the variables.

Operational variables (or operationalizing definitions) refer to how you will define and measure a specific variable as it is used in your study. This enables another psychologist to replicate your research and is essential in establishing reliability (achieving consistency in the results).

For example, if we are concerned with the effect of media violence on aggression, then we need to be very clear about what we mean by the different terms. In this case, we must state what we mean by the terms “media violence” and “aggression” as we will study them.

Therefore, you could state that “media violence” is operationally defined (in your experiment) as ‘exposure to a 15-minute film showing scenes of physical assault’; “aggression” is operationally defined as ‘levels of electrical shocks administered to a second ‘participant’ in another room.

In another example, the hypothesis “Young participants will have significantly better memories than older participants” is not operationalized. How do we define “young,” “old,” or “memory”? “Participants aged between 16 – 30 will recall significantly more nouns from a list of twenty than participants aged between 55 – 70” is operationalized.

The key point here is that we have made it absolutely clear what we mean by the terms as they were studied and measured in our experiment. If we didn’t do this, then it would be very difficult (if not impossible) to compare the findings of different studies to the same behavior.

Operationalization has the great advantage of generally providing a clear and objective definition of even complex variables. It also makes it easier for other researchers to replicate a study and check for reliability .

For the following hypotheses, name the IV and the DV and operationalize both variables.

1. Women are more attracted to men without earrings than men with earrings.


D.V. ____________________________________________________________

Operational definitions:

I.V. ____________________________________________________________

2. People learn more when they study in a quiet versus noisy place.

I.V. _________________________________________________________

D.V. ___________________________________________________________

3. People who exercise regularly sleep better at night.

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Independent and Dependent Variable Examples Across Different Disciplines

Flowers Independent and Dependent Variable Examples

A variable is something that researchers are studying in a research project or experiment. Every scientific experiment involves at least one independent variable and one dependent variable. Discover the difference between these two types of variables and review several examples of each type.

Independent vs. Dependent Variables

Well-designed research projects require different types of variables. But what's the difference between independent and dependent variables? Their definitions can help you see the differences.

The researcher determines whether manipulating the independent variable leads to different outcomes regarding the dependent variable. Basically, the dependent variable depends on the independent variable (also known as a treatment variable).

Independent and Dependent Variables Examples

There are many independent and dependent variables examples in scientific experiments, as well as academic and applied research . You even use these variables in your daily life! For example, when you try out a new workout routine or diet (the independent variable), you measure how beneficial it was in your day (the dependent variable). Take a look at these independent and dependent variables examples in multiple disciplines.

Carb Loading and Endurance

An exercise physiologist wonders if carb loading (eating a lot of carbohydrates) the day before participating in endurance activities (such as triathlons or marathons) impacts performance.

Cancer Medicine

A scientist studies the impact of a drug on cancer. She administers the drug to a research group and a placebo to a control group.

Rats and Affection

A scientist studies the impact of withholding affection from rats. One group receives a lot of affection, while the other receives none.

Language Mastery

A researcher explores whether people who already speak multiple languages learn new languages faster than people who only speak one language.

Education and Earnings

A researcher wants to know if education level impacts how much a person earns in their job. She studies the amount of education a person has in their life to their current earnings.

National Origin and Net Worth

A social scientist wonders if there is an association between a person's national origin and their wealth, measured as net worth.

Time Spent Studying and Academic Success

An educational researcher explores whether there is a link between the amount of time someone spends studying and the grade they get in a particular class.

Job Satisfaction and Pay

A human resources professional wonders if how much money a person earns can impact the extent to which an individual experiences job satisfaction.

Sunlight and Plant Growth

A botanist wonders if the amount of direct sunlight a plant receives impacts how quickly it grows.

Airline Travel and Influenza Infection

A medical researcher wonders if the amount of airline travel a person engages in impacts how likely they are to catch influenza during flu season.

Chiropractic Treatments and Migraines

A scientific researcher wonders if regular chiropractic care decreases the frequency and/or severity of migraine headache episodes

Socioeconomic Status and Number of Children

A social scientist explores if there is a link between socioeconomic status and the number of children someone has.

News Viewership and Knowledge of Facts

A media studies researcher wonders if the amount of time a person spends watching television news contributes to how much factual information people know about current events.

Making Sense of Variables

Scientific research questions, experiments and statistical data analysis can get very complex. Learning how to recognize the difference between independent and dependent variables will provide you with a strong foundation before you start learning about other types of variables . To further expand your research skills, review some examples of research paper purpose statements .


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