Why is it important to have control over all other variables other than independent and dependent?

Q: Why is it important to control other variables other than the independent and dependent ones?

If you dont control relevant extraneous variables, they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable.

Difference between Dependent Variable and Independent Variable

The difference between dependent and independent variables is that the dependent variable changes with changes in the independent variable. Therefore, if variations are observed in a variable in correlation with another variable, they are categorized into dependent and independent variables in research, psychology, or experimental investigations. Hence, the independent variable is manipulated and controlled in experiments to explore its effects on the dependent variable.
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Difference between Dependent Variable and Independent Variable
Comparative Table
What is a Dependent Variable?
What is an Independent Variable?
Dependent Variable vs Independent Variable – Infographics
Similarities
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Why is it important to control other variables other than the independent and dependent ones?
Why is it important to control all other variables?
Why is it important that all other variables other than independent remain constant?
Why is there a need to control other variables except the independent variable in an experiment?

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Source: Dependent Variable vs Independent Variable (wallstreetmojo.com)

The dependent variable vs independent variable in research or psychology research portrays the prime difference between a dependent and independent variable significant in the experimental investigations.
The independent variable is not affected positively or negatively in response to changes in other variables in the study.
The dependent variable depends on the independent variable. Therefore, a change in the independent variable can cause a change in the dependent variable.
Researchers manipulate and control independent variables to study how the dependent variables react to them. Essentially, the independent variable is the cause, and the dependent variable manifests the effect.

Comparative Table

Particulars	Dependent Variable	Independent Variable
Definition	It refers to the variables dependent on other variables in the study and changes with updates in the other variables.	It refers to the standalone variables that do not depend on other variables in the study.
Purpose	It is explored in the study. Changes or effects are measured by observing the dependent variables.	Experimental independent variables are subjected to manipulations in the study to create effects on the dependent variables.
Variation	Unintentional changes can happen to the dependent variables in reaction to the independent variables.	Variables that the researcher can control. Researchers intentionally create variations.
Applications	To study the responses to the changes produced in other variables. It exhibits the outcomes that are required to measure in experiments.	It can explain outputs and predict the values of dependent variables. In addition, it showcases the causes behind any changes or results.
Examples	Exam score, plant growth, and weight loss.	Time spent studying, sunlight for plants, and exercise.
Synonyms	The response variable, Predicted variable, Measured variable, Explained variable, Experimental variable, Responding variable, Outcome variable, and output variable.	Predictor variable, Manipulated variable, Explanatory variable, Exposure variable, Input variable.

What is a Dependent Variable?

A dependent variable is an element in a study, research, or statistical model that depends on a specific independent variable. It is also known as the outcome variable since it is the outcome that the researchers seek and measure using an independent variable. It is an important input in defining the result of an experiment. A dependent variable is dynamic and therefore showcases the change, effect, impact, or influence of the change made in the independent variable.

A simple example of a dependent variable in a study will be the calories burnt in a workout session; here, the calories are a dependent variable because it depends on the workout, whereas the training itself is an independent variable and stands alone. Any change or manipulation in the activity, like time duration, type of exercise, amount of effort, etc., influences or changes the dependent variable.

What is an Independent Variable?

The independent variable is the standalone element in an experiment and does not respond to or depend on any other element. It represents the cause behind any change being measured or consequences in the research model. It is utilized to explore its impact, influence, and change reflected in or exhibited by the dependent variable.

For example, in an experiment to see how different types of food fed to a man affect his body and health, the food tried is categorized into healthy and unhealthy food. Here health is the dependent variable shaped by the independent variable, the food provided. It is clear that the human is the model or system in which both variables operate, and the analyst measures the output variable, health.

Dependent Variable vs Independent Variable – Infographics

Similarities

Both variables change at almost the same time. So, plotting an independent variable vs dependent variable graph will not give a line perpendicular to the x-axis or y-axis.
Both variables are not constants. For instance, in an independent variable vs dependent variable example from the retail sector, the value of retailers formed in the mind of consumers is a dependent variable that changes with independent variables like price, assortment, and convenience.
Both are equally important in solving research problems. The dependent variable manifests the effect, and the independent variable represents the cause.
An experimental investigation can have more than one dependent and independent variable.

Why is it important to control other variables other than the independent and dependent ones?

If you don't control relevant extraneous variables, they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable.

Why is it important to control all other variables?

In experiments, a researcher or a scientist aims to understand the effect that an independent variable has on a dependent variable. Control variables help ensure that the experiment results are fair, unskewed, and not caused by your experimental manipulation.

Why is it important that all other variables other than independent remain constant?

If these are not kept constant, then it is impossible to determine the effect of the variable that you are intending to test.

Why is there a need to control other variables except the independent variable in an experiment?

The researcher wants to make sure that it is the manipulation of the independent variable that has changed the changes in the dependent variable. Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.