Independent And Dependent Variables In Thesis

As its name suggests, an independent variable is one which remains unaffected by other variables.Alternately known as the predictor variable, explanatory variable, controlled variable. I am of the opinion that these terms are frequently used inappropriately.

As its name suggests, an independent variable is one which remains unaffected by other variables.

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It is something that the experimenter observes during an experiment and is influenced by the experiment.

It is expected to change in response to some other factors.

it is variable that measures the effect of independent variable on the test units.

It is also known as the criterion or measured variable.

In a scientific experiment, the independent variables are controlled or changed whereas the dependent variables tend to be measured and tested.

An independent variable is the one that does not rely on anything else and hence can be manipulated, while the dependent shows the effect, of changes made to the independent variable.The revised value of the dependent value depends on the independent variable.There can be multiple dependent variables for one independent variable.The dependence of the former on the latter is being examined by the statistical models.So, here in this article, we are going to discuss some important points of difference between independent and dependent variable.The two most common types of variable are dependent variable and independent variable.A variable is said to be independent, whose change influence another variable, while if the variable is dependent, it will change in response to the change in some other variable.I am very interested in learning how YOU define these terms to students in your classes. I shall post to the list a summary of responses received. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Karl L. Wuensch, Department of Psychology, East Carolina University, Greenville NC 27858-4353 Voice: 252-328-4102 Fax: 252-328-6283 Wuensch [email protected] the years I have become increasingly uncomfortable with the way many people use the terms "independent variable" and "dependent variable." I now believe that these terms should be used only when referring to experimental research, that is, research where the independent variable(s) is(are) manipulated and the dependent variable(s) is(are) passively observed.Researchers commonly associate the term "independent variable" with "cause" and "dependent variable" with "effect." Using the terms "independent variable" and "dependent variable" with nonexperimentally gathered data may prod researchers in making causal attributions when they should not. Several years ago I was assisting a doctoral student with his dissertation.He was investigating the correlates of a single outcome variable which was treated as continuous.Among his predictor variables were several categorical variables. holding researchers have told me that if they analyze their data with an independent samples t (where the grouping variable is called the "independent variable"), then "significant" results show that the "independent variable" caused changes in the "dependent variable," but that if they analyze their data with a correlation/regression analysis, then they cannot interpret a significant association as evidence of causation - you know, that old "correlation does not imply causation" bullshit (see Help/).