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Beginning R pp 165-183 | Cite as

Correlation and Regression

  • Larry Pace

Abstract

In Chapter 12 you learn simple (bivariate) correlation and regression. You discover how to use the R functions for correlation and regression and how to calculate and interpret correlation coefficients and regression equations. You also learn about fitting a curvilinear model and about confidence and prediction intervals for regression models. In Chapter 13, we will build on what you learn here, with multiple correlation and regression. In Chapter 13, you will also learn that ANOVAs and t tests are special cases of regression. All these techniques are based on the same underlying general linear model.

Keywords

Quadratic Model Prediction Interval Plot Function Positive Covariance Negative Covariance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Larry Pace 2012

Authors and Affiliations

  • Larry Pace

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