The equation for simple regression has the general form $$Y = b_1X_1$$. In this formula, $$Y$$ represents the predicted score on the outcome variable, $$X_1$$ represents the individual's score on the predictor variable, and $$b_1$$ represents the regression weight or the slope of the line.

Simple Regression Formula

An example of simple regression involves predicting a student's grade point average (GPA) based on their intelligence quotient (IQ) score. Once correlational research establishes a relationship between IQ and GPA, researchers can apply a simple regression equation to calculate an individual's expected GPA given their specific IQ score.

Example of Simple Regression: IQ and GPA

What is the defining characteristic of simple regression?

Simple regression is a statistical technique that involves using exactly one predictor variable to predict the value of a single outcome variable.

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In regression analysis, the outcome variable—also referred to as the criterion variable—is the variable that is being predicted by the model.

Outcome Variable or Criterion Variable

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KPU Research Methods in Psychology - 4th American Edition

Simple Regression

Multiple regression is a statistical technique that extends simple regression by measuring several predictor variables ($$X_1, X_2, X_3, \dots, X_i$$) and using them to predict a single outcome variable ($$Y$$). It can also be utilized to describe the complex relationship between the outcome variable and a set of predictors. The result of this analysis is an equation that expresses the outcome variable as an additive combination of all the measured predictor variables.

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