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The Power of Anonymous Surveys
March 22, 2023
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In experimental research, a Variable is a factor that can change and can be changed. These factors can be altered and controlled for an experiment to measure the effect of one variable on the other.Â
The experiment includes different types of variables. The aim of an experiment is to determine the causal relationships between two or more variables. Among many types of variables two of which we will discuss are Explanatory Variables and Response Variables.
An Explanatory Variable is a factor that has been manipulated in an experiment by a researcher. It is used to determine the change caused in the response variable. An Explanatory Variable is often referred to as an Independent Variable or a Predictor Variable.Â
Response Variable is the result of the experiment where the explanatory variable is manipulated. It is a factor whose variation is explained by the other factors. Response Variable is often referred to as the Dependent Variable or the Outcome Variable.Â
For Example,Â
You want to find out if alcohol decreases the ability to drive safely. The alcohol a participant consumes determines its effect on their driving performance. In the experiment, the amount of alcohol consumed gives an explanation for the driving skill.
Therefore in the experiment,
The best way to identify the two variables separately and understand the difference is to remember that You change the value of Explanatory Variables to observe the impact it has and how it influences the Response Variable.Â
Explanatory Variable explains the variation caused in Response Variable. There is a cause-and-effect relationship between the two variables. The number of variables in each type may be more than one depending upon the research question.
You want to observe if Protein Shake helps in losing weight. So the aim is to determine the change in your weight caused by the intake of protein shake.
You want to observe the amount of time spent on watching T.V. impacts the score earned by the students on an exam.Â
How does diet affect the health of your Skin and Hair?
In this experiment, you observe how the diet causes changes in the health of your skin and hair. So, in this case
An Explanatory Variable is often called an Independent Variable. However, both the terms have a slight difference in the way they are used in experimental research.Â
A variable that is independent should not be affected by or depend on any other variable present in the experiment. An Independent variable can only be manipulated by the experimenter. Let’s say you control the amount of alcohol each participant consumes in the experiment, this makes alcohol an Independent Variable.Â
When the variable is not independent on its own, it is called an Explanatory Variable. In real-world observation, independent variables are influenced by other variables present. These experiments are observational and so, Explanatory Variable is a much-preferred term.Â
For example,Â
Let’s say you are observing the impact of two variables – balanced diet and physical activity – on weight loss. You may think that diet and physical activity are not dependent on each other, but they are.Â
Although the two Explanatory variables, balanced diet and physical activity are not completely dependent on one another they explain the changes caused in the Response variable that is weight loss.Â
So in such an observational experiment, these factors are called Explanatory Variables that affect weight loss that is Response Variable.
When you have paired data you may use Scatterplot to demonstrate the causal relationship between the Explanatory and Response Variables.Â
A paired data implies that you have one variable for each type. This means that the outcome of every response variable for each participant is linked with every explanatory variable.Â
In such a case, in a scatterplot, the Explanatory Variable is plotted along the X-axis, i.e., horizontal axis. Response Variable is plotted along Y-axis, i.e., the vertical axis of a Cartesian coordinate system.Â
Let’s say you want to observe if there is any causal relationship between the number of hours spent studying and the performance on the test. You experiment on 100 students in a school.Â
You can demonstrate the result in a scatter plot by plotting the hours spent on studying on the X-axis and the test score on the Y-axis. Each data point in the scatterplot is the paired data of each student.Â
The way to differentiate between Explanatory Variable and response Variable isÂ
In a Scatterplot, each data point represents an individual participant of the experiment. The Explanatory Variable is plotted on the X-axis and the Y-axis represents the Response Variable.
Explanatory Variable in experimental research is also referred to as – independent Variable and Predictor Variable.
The other terms used to refer to Response Variable are – Dependent Variable and Outcome Variable.
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