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Section 11.6 Glossary
- regression
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A method for estimating coefficients that fit a model to data.
- response variables
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The variables a regression model tries to predict, also known as dependent variables.
- explanatory variables
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The variables a model uses to predict the response variables, also known as independent variables.
- simple regression
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A regression with one response variable and one explanatory variable.
- multiple regression
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A regression with multiple explanatory variables, but only one response variable.
- coefficients
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In a regression model, the coefficients are the intercept and the estimated slopes for the explanatory variables.
- categorical variable
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A variable that can have one of a discrete set of values, usually not numerical.
- control variable
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A variable included in a regression to separate the direct effect of an explanatory variable from an indirect effect.
- generalized linear models
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A set of regression models based on different mathematical relationships between the explanatory and response variables.
- logistic regression
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A generalized linear model used when the response variable has only two possible values.
