Titlebook: Business Analysis Using Regression; A Casebook Dean P. Foster,Robert A. Stine,Richard P. Waterman Textbook 1998 Springer Science+Business M

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Prediction and confidence intervals in regression,ression is similar to that of the confidence intervals developed in ., the regression model itself is more complex and complicates the interpretation of the intervals. In addition, similar intervals known as prediction intervals provide estimates of the accuracy of predictions from the fitted model.

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Multiple regression,r prediction by again filling in values for the explanatory variables. The confidence intervals and tests for these coefficients closely resemble their counterparts covered in Class 3, and the multiple correlation . and residual standard error again measure the goodness-of-fit of the equation.

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Modeling Categorical Factors with Two Levels,umerical variable, known as a dummy variable. Since these dummy variables are numerical representations of qualitative, not quantitative, information, the coefficients of dummy variables require special interpretation. The testing methods of Class 5 are valuable tools for comparisons among models using qualitative factors.

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