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A predictor variable, not to be confused through its similarities with independent variable, is used in efforts to predict an outcome. The difference comes from the predictor variables not being manipulated by the researcher, but rather naturally occurring changes. In other words, this would be looking at a variable as it naturally happens and how influences the second variable. The x range is the predictor variable, an example of that is ice cream sales and y range being the temperature outside. A regression line could show a percentage of ice cream sales explained by the temperature outside that day. With one variable being the predictor variable, the other is criterion or dependent variable as the response in the relationship of the two. Overall, these variables are used in as a statistical method to better understand the relationship between the two (Gravetter, Wallnau, Forzano & Witnauer, 2021).
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