The Terminology of Statistical Analysis

January 1, 2003

1 Min Read
The Terminology of Statistical Analysis

Originally Published MX January/February2003


Multiple regression is a method of explaining the linear relationship between several independent, or predictor, variables and a dependent, or criterion, variable. Multiple regression enables a researcher to seek a trustworthy answer to the question, What is the best predictor of ______? The statistical analytical technique determines the linear relationship between the values that change, and then finds an equation that satisfies such a relationship.

R-square is an indicator of how well the model fits the data, and is a value expressed as a decimal term between 0 and 1. An R-square of 0.4 means that 40% of theoriginal variability has been explained, and the re-maining 60% cannot be explained by these variables in the equation.

Coefficients are the multipliers in front of the independent variables in the equation. The higher their value, the more impact on the dependent variable they are trying to predict (in the case presented here, market capitalization). Those with especially high values are referred to as

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