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. Show
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. Published on September 19, 2022 by Rebecca Bevans. 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. Example 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:
Types of data: Quantitative vs categorical variablesData 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 variable can be broken down into further types. Quantitative variablesWhen 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. Discrete vs continuous variables
Categorical variablesCategorical 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. Binary vs nominal vs 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 sheetTo 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.  Parts of the experiment: Independent vs dependent variablesExperiments 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. Independent vs dependent vs control variables
Example data sheetIn 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. 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. 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. Receive feedback on language, structure and formattingProfessional editors proofread and edit your paper by focusing on:
See an example Other common types of variablesOnce 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 variable are listed below.
Frequently asked questions about variablesWhat are independent and dependent variables? 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. What is a confounding variable? 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. What is the difference between quantitative and categorical variables? 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. Cite this Scribbr articleIf you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.
Is this article helpful?You have already voted. Thanks :-) Your vote is saved :-) Processing your vote... What is the term for a measurable trait or characteristic that is subject to change under different conditions?Variable. A measurable trait or characteristic. that is subject to change under. different conditions.
What is a characteristic that is subject to change?In the context of scientific experiments, a variable is any factor that could change or be changed. So, for instance, if you're measuring how effective a medication is, variables could include the amount of dosage, how frequently it's taken, and the characteristics of each test subject, such as their age and weight.
What is a characteristic that reflects a change?dependent variable. a characteristic that reflects a change. intervening variable. a variable that changes the relationship between an independent and a dependent variable. correlation.
What are the 3 types of variables?There are three main variables: independent variable, dependent variable and controlled variables. Example: a car going down different surfaces.
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What do you call a characteristic that can differ in a measurable way and cause change in something else?
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