1 / 11

Solutions to Tutorial 6 Problems

Solutions to Tutorial 6 Problems. 1. The matrix plot of the Milk Production Data. The linearity assumption is ok. The measurement error assumption: a). Normality: seems ok b). Mean zero: ok

wang-maxwell
Télécharger la présentation

Solutions to Tutorial 6 Problems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Solutions to Tutorial 6 Problems 1. The matrix plot of the Milk Production Data

  2. The linearity assumption is ok. • The measurement error assumption: • a). Normality: seems ok b). Mean zero: ok • c). Independence: seems ok d). Homogeneity: slightly violated. • The predictor assumption: • a). Nonrandom: violated b). No measurement errors: unknown • c). Linearly independence: not violated. • 4. The observation assumption: violated. There are some outliers.

  3. The matrix plot of the Right-to Walk Laws Data

  4. The linearity assumption is ok. • The measurement error assumption: • a). Normality: seems violated b). Mean zero: ok • c). Independence: seems ok d). Homogeneity: slightly violated. • The predictor assumption: • a). Nonrandom: violated b). No measurement errors: unknown • c). Linearly independence: not violated. • 4. The observation assumption: seems violated. There are 3 outliers.

  5. The matrix plot of the Egyptian Skulls Data

  6. The linearity assumption seems violated. • All other assumptions can not be checked.

  7. The matrix plot of the Domestic Immigration Data

  8. The linearity assumption is ok. • The measurement error assumption: • a). Normality: seems ok b). Mean zero: ok • c). Independence: seems ok d). Homogeneity: seems ok. • The predictor assumption: • a). Nonrandom: violated b). No measurement errors: unknown • c). Linearly independence: not violated. • 4. The observation assumption: seems violated. There are outliers.

  9. The matrix plot of the New York Rivers Data

  10. The linearity assumption is ok. • The measurement error assumption: • a). Normality: seems violated b). Mean zero: ok • c). Independence: seems ok d). Homogeneity: seems ok. • The predictor assumption: • a). Nonrandom: unknown b). No measurement errors: unknown • c). Linearly independence: not violated. • 4. The observation assumption: seems violated. There are some outliers.

  11. 2. a) The SLR fit results in the following: The regression equation is Minutes = 37.2127 + 9.96950 Units S = 18.7534 R-Sq = 89.7 % R-Sq(adj) = 89.2 % Analysis of Variance Source DF SS MS F P Regression 1 67084.8 67084.8 190.749 0.000 Error 22 7737.2 351.7 Total 23 74822.0 Assumptions Violated: 1). The Linearity Assumption is violated 2). All other Assumptions can not be checked since linearity is violated.

More Related