Please feel free to make appointments to see me at other times.

Office: 209A LeConte College

Phone: 777-5346

E-mail: hitchcock@stat.sc.edu

**Current Textbook:***Applied Linear Statistical Models, 5th edition*, by Kutner, Nachtsheim, Neter and Li (4e: J. Neter, M.H. Kutner, C.
Nachstheim, and W. Wasserman).

**Course Description:****701—Applied Statistics II. (3)** (Prereq: STAT 700 or consent of department) Continuation
of STAT 700. Simple linear regression, correlation, multiple regression, fixed and
random effects analysis of variance, analysis of covariance, experimental design, some multivariate methods,
various statistical packages.
Not to be used for
M.S. or Ph.D. credit in statistics
or mathematics.

__ Purpose:__
To expand the methodological abilities of future scientists in the experimental,
social, and professional sciences beyond what is usually learned in a basic course.

Topics Covered | Time | |

Review of simple linear regression and correlation | 1 week | |

Multiple linear and polynomial regression: model fitting, formal inferences | 3 weeks | |

Model building; Collinearity and influence; regression diagnostics | 1 week | |

One-factor ANOVA, multiple comparisons, random effects models | 1.5 weeks | |

Two-factor crossed ANOVA; fixed, random, and mixed models | 23.1-23.4 (4e: 22.1-22.4), 25.1-25.4 (4e: 24.1-24.4) |
2.5 weeks |

Randomized complete block designs, balanced incomplete block designs, Latin square | 28.3-28.6 (4e: 30.1-30.5) |
1.5 weeks |

Analysis of Covariance | 1 week | |

Nested Analysis of Variance | 1.5 weeks |

__ Available Computing Resources:__
R is available as a free download from the CRAN home page) and students who want SAS can buy
a copy from USC Computer Services.

These packages are also available on the computers in the labs in LeConte College (and a few other buildings). Help in using R can be found on the CRAN home page.

- Introduction to SAS which should be a good instruction for the software

**Computer Code for Class Examples**

- SAS example: Diagnostics for Model Specification, Outliers and Influential Observations (life insurance data, body fat data, surgical unit data)

- R example: Diagnostics for Model Specification, Outliers and Influential Observations (life insurance data, body fat data, surgical unit data)

- SAS example: Single-Factor ANOVA (Kenton Foods data)

- R example: Single-Factor ANOVA (Kenton Foods data)

- SAS example: Two-Factor ANOVA (Castle Bakery data)

- R example: Two-Factor ANOVA (Castle Bakery data)

- SAS example: Two-Factor ANOVA (Interaction Present) (Melon data)

- SAS example: Two-Factor ANOVA (One Observation Per Treatment) (Insurance data)

- SAS example: Randomized Complete Block Design (Executive data)

- SAS example: Balanced Incomplete Block Design (Taste Test data)

- SAS example: Latin Square Design (Bank Teller data)

- SAS example: Analysis of Covariance (Cracker data)

- SAS example: Nested Designs (Training School data)

**Data Sets**

- Training Data Set (not the same data as in the book's example!)

**Homework**

- Homework 1 (due Friday, Feb. 2)

- Homework 2 (due Friday, Feb. 16)

- Homework 3 (due Friday, March 2)

- Homework 4 (due Friday, March 23)

- Homework 5 (due Friday, April 13)

- Homework 6 (due Thursday, April 26 by 3 p.m.)

**SAS Code for Homework**

(Past students can email me for these files.)

- Final Exam Review Sheet (use this plus first two review sheets)

- Midterm 1 (Wednesday, Feb. 21) (Note this change.)
- Midterm 2 (Wednesday, March 28)
- Final Exam (Friday, May 4, 2:00 p.m.)