A Comprehensive Guide about Explanatory Variables and its Types

Introduction

No research is complete without variables. This statement is right for every kind of research, whether academic or non-academic research. Without variables, you cannot predict the relationship of the problem. Researchers often measure the relationship between variables through experiments and observations in research. This relationship is important to investigate the research problem at hand. Now, there are many types of variables that you use in research. The explanatory variables are one of those variables.

Many of you may have heard about this word for the first time. You do not need to worry; it is the same variable that you work with often in your research but do not know. Today’s article is all about explaining explanatory variables. There will be a description of its types too. Hence, you can say that this article will be a complete guideline about these variables. Thus, let’s start our discussion with the following very basic question;

How many variables are there?

Scientists use experiments and observation to study the cause and effect. To get the desired results, the researcher alters many things. The things that he can alter are called variables. In research, an investigator has to deal with different variables, no matter if he is working on his own or hiring a PhD dissertation writing service. A brief description of all the types is as follows;

Independent or explanatory variables

The first variable type is the independent variable, often called the explanatory variable. The explanatory variables are the ones that the researcher alters to get desired results. A good experiment has only one independent variable to ensure a fair test. The data collected by the researcher is recorded as the independent variable is changed.

Dependent or response variable

The second type of variable you see in research is the dependent variable. It is also called the response variable. It responds to the change in the independent variable. Whenever the researcher makes a small change in the explanatory variables, this variable reacts. It changes and explains the effect. An example of this variable is as follows;

A researcher tries to determine whether academic motivated motivation is related to Grade Point Average (GPA). In this study, the GPA is not changeable. It depends on the academic motivation of the students. So, the GPA is the dependent or response variable.

Controlled variable

The third and last type of research variable is the controlled variable. It is such a variable that you can control and keep constant throughout the research process. These variables also need constant attention as explanatory variables. It is because these are the constant variables, and any change in these can alter the results of your research. Therefore, you must be able to control them in all ways. An example of this variable is as follows;

For example, a researcher wants to know how much the water flow increases when he opens the faucet. He also knows that water flow can change due to pressure. Therefore, he keeps the pressure constant at some value. Here, the water pressure is a controlled variable.

What are explanatory variables in research?

In research, the researchers have to deal with a lot of variables. You might have heard about only dependent or independent variables. The same is the case with these variables. If you know about independent variables, you also know about explanatory variables. It is because the second name of this variable is an independent variable.

An explanatory variable is what you manipulate or observe changes in. You can also say that this variable is the cause and explains the results. You expect changes in other variables when there is a change in this variable. This also proves that it is an independent variable.

Identification of explanatory variables

Until now, you know what these variables are. One thing that you do not know is how to identify explanatory variables in research. Below are some of the questions you should ask yourself to identify them;

• Is it the variable that researchers are manipulating and changing again and again in research?
• What variable do researchers change to observe the change in other variables?
• Which variable is the one that cannot be changed and is influencing the other variables?

By effectively answering these questions, you can identify the explanatory variable easily.

What are some good examples of explanatory variables?

As described earlier, no research is complete without variables. In every research, you will see some independent and some dependent variables. You must remember that independent variables are explanatory variables. Now, let’s look at some of the examples of these variables for a better understanding.

Example no. 1

A researcher might want to test whether caffeine improves speed. To study this, you provide the participants with different doses of caffeine and record their reaction time. Now in this study, the explanatory variable is “caffeine dose.” You can manipulate this variable and change it according to the situation.

Example no. 2

COVID-19 is prevalent nowadays in the world. It is changing the face of the world through its deadly attacks. Due to this, a researcher might want to research this subject. His research title can be “Does the weather affect the transmission of COVID-19.” Now, here in this example, weather parameters are explanatory variables. Those parameters are humidity, temperature, and wind.

Example no. 3

A group of middle school kids wants to see if they can forecast age by measuring their height. They randomly select 50 persons from their school, both kids and teachers, and measure their height and age. The explanatory variable is the height, which will differ for different participants.

Conclusion

Variables play an important role in any research, especially explanatory variables. They are the independent variables that you can manipulate to get the desired results. Other variables are also important in their places. Also, you can identify an explanatory variable by following the steps mentioned above. The examples given above can strengthen your understanding of the explanatory variable.