## Applied linear regression models |

### What people are saying - Write a review

#### Review: Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences)

User Review - May - GoodreadsAmong books on this topic, this one is pretty good. For those that may not have obtained the material sequentially, the appendix is recommended. I can see some giving it lower marks, as it does not ... Read full review

#### Review: Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences)

User Review - Jerzy - GoodreadsPretty clear - does a really decent job of introducing the concepts of regression and presenting the most important proof concepts without giving too much detail for an applied book. Lots of good problems to work through. Read full review

### Common terms and phrases

95 percent confidence appropriate approximate column conclusion confidence interval confidence limits Cook's distance correlation data set decision rule degrees of freedom denoted error sum error terms error variance estimated regression coefficients estimated regression function estimated standard deviation explanatory variables family confidence coefficient Figure fitted regression function fitted values follows Hence least squares estimates likelihood function linear regression function linear regression model logistic regression logistic regression model lowess maximum likelihood estimates mean response MINITAB multicollinearity nonlinear regression normal distribution normal probability plot observations ordinary least squares outlying P-value percent confidence interval prediction interval probability distribution Problem procedure random variables reduced model Refer regression analysis regression model 2.1 residual plot response function response variable sampling distribution scatter plot set in Appendix simple linear regression SSTO standard deviation subset sum of squares Table test statistic Toluca Company example transformed variance-covariance matrix vector weighted least squares