Independent & Dependent Variables

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Independent & Dependent Variables
 Independent Variables are things you can NOT change such as gender, age, grade, ethnicity, SES etc.  This is the “cause”.  In non-experimental research when cause cannot be determined, this variable is often referred to as the Predictor variable.
Dependent Variables are things you CAN change (or at least have an effect on) such as aptitude, test scores, attitudes etc.  This is the “effect”. In non-experimental research when the cause/effect relationship cannot be determined, this is often referred to as the Criterion variable.
Variables can appear as categorical variables or continuous variables.
Categorical variables appear as nominal or ordinal scales.
Nominal scales define types or names of categories, such as Red or White  or Male or Female.  When there are only two choices, these are also called dichotomous variables.  Nominal scales can include more than two choices such as Candidate Party (Democrat, Republican or Independent).
Ordinal scales define categories that appear in a specific order, such as levels of Karate belt (White, Yellow, Brown, Black) or  BMI Weight classification (Underweight, Healthy, Overweight, Obese, Extremely Obese) .
Continuous Variables appear on a continuous interval or ratio scale.
An Interval Scale includes zero that does not mean the absence of what is being measured. For example, temperature can appear on a range above and below zero, where zero has a value.
A Ratio Scale includes zero, meaning the absence of what is being measured. For example, the number of minutes spent exercising can appear as 0 (meaning no minutes) upwards.
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