STAT 516 (Statistical Methods II)

Spring 2008

Syllabus

Syllabus: (Word document) or (pdf file)

Instructor

David Hitchcock, assistant professor of statistics

Office Hours -- Spring 2008

Mon 11:00-12:00, Tues 1:30-2:30, Wed 11:00-12:00, Thu 10:00-11:00, Fri 1:30-2:15.
or please feel free to make an appointment.

209A LeConte College
Phone: 777-5346
E-mail: hitchcock@stat.sc.edu

Class Meeting Time

MWF 12:20PM - 1:10PM, LeConte College, Room 210A

Purpose: To complete a basic two course sequence (in conjunction with STAT 515 or 509) in statistical techniques available to the general practitioner for analyzing experimental data. To introduce students in many different disciplines to multiple regression and analysis of variance for basic experimental designs. To provide students with the knowledge to implement and interpret these standard linear models.

Current Textbook: Statistical Methods, Second Edition, by R.J. Freund and W. J. Wilson, Academic Press, 2002.

Homework

Data Sets

Some Output for Homework

STAT 516 Supplementary Material

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).
SAS is available in LC 124 and possibly PSC 109. R is available in LC 124 and LC 303A. Help in using R can be found on the CRAN home page.

Downloading Instructions for R

Computing Tips: Some Review

Computer Code for Class Examples

Statistical TopicExample in SAS Code Example in R Code
Simple Linear Regression
and Correlation
(Chapter 7)		 SAS example: (House data)
Output for SAS example 		R example: (House data)
Output for R example
Multiple Linear Regression
(Chapter 8)		 SAS example (California rain data)
Output for SAS example 		R example (California rain data)
Output for R example
Transformations
(Chapter 7-8)		 SAS example (surgical data)
Output for SAS example 		R example (surgical data)
Output for R example
One-Way Analysis of Variance
(Chapter 6)		 SAS example: (Rice data)
Output for SAS example 		R example: (Rice data)
Output for R example
Two-Way ANOVA & Factorial Experiments
(Chapter 9)		 SAS example (Gas mileage data)
Output for SAS example 		R example: (Gas mileage data)
Output for R example
Randomized Block Design
(Chapter 10)		 SAS example (Wheat data)
Output for SAS example 		R example (Wheat data)
Output for R example
Randomized Block Design with Sampling
(Chapter 10)		 SAS example: (Rubber data)
Output for SAS example 		R example: (Rubber data)
Output for R example
Latin Square Design
(Chapter 10)		 SAS example (Productivity data)
Output for SAS example 		R example: (Productivity data)
Output for R example
Analysis of Unbalanced Data
(Chapter 11)		 SAS example (Table 11.2 data)
Output for SAS example 		R example (Table 11.2 data)
Output for R example
Analysis of Covariance (ANCOVA)
(Chapter 11)		 SAS example (Trigonometry scores data)
Output for SAS example 		R example (Trigonometry scores data)
Output for R example
Logistic Regression
(Chapter 11)		 SAS example (TIF data)
Output for SAS example 		R example (TIF data)
Output for R example
HELPFUL SAS RESOURCE:

TROUBLESHOOTING:

Review Sheets

Practice Problems for the Final Exam: Data Sets

Formula Sheets

You may bring to the first exam one standard-sized sheet of paper with anything you want written on it (for example, you should write any formulas you may need).

You may bring to the second exam one standard-sized sheet of paper with anything you want written on it (for example, you should write any formulas you may need).

You may bring to the final exam THREE standard-sized sheets of paper with anything you want written on them (for example, you should write any formulas you may need).

Exam Solutions

Exams