Statistics 325/425

Data Analysis and Linear Models

Syllabus, Fall 2006

Classes: 2:45-4:00 pm Tuesday and Thursday at Yost 300.

Instructor: Professor Jiayang Sun, Yost 326, 368-0630, jsun at case edu

Office Hours: 4:00-5:00pm Tuesday and Thursday @ Yost 326.

Teaching Assistant: Peng Liu, Yost 230, 368-0416, peng.liu at case.edu

Office hours: 1:30-3:30pm Wednesday, 10:00am - 12:00pm Friday @ Yost 234 (368-2656).

Other TA's hours: http://stat.case.edu/tutor-schedule.htm

Course Outline:

The sequence of Stat 325/425-326/426 introduces classical and modern applied statistics. It is designed for students who have some knowledge of statistics but are still not clear what to do when confronted with data. Stat 325/425, the first part of the sequence, covers basic exploratory data analysis for univariate (response) observations with or without single or multiple covariates. Graphical methods and data summarization are followed by model-fitting using R/S-plus computing language. Topics include simple and multiple regression, transformation, model selection, diagnostics, robust procedures, ANOVA and analysis of covariance and interpretation of results. Some non-traditional approaches and biases in sampling and data analysis will be discussed at the end of semester (time permitting). Lectures include case studies, computer demonstration and group discussion.

Prerequisite: Matrix Algebra such as Math 201 and Some Basic Statistics* such as STAT207/208 (or STAT 243, or STAT 312, or one of EPBI 431/441/458).

Text Books:

Required: Weisberg, Sanford (2005). Applied Linear Regression, 3rd edition. Wiley; ISBN: 0-471-66379-4. (Author's Web Site for Software Info)

Recommended:

R.G. Miller, R.J.Miller and B.W. Brown (1996). Beyond ANOVA: Basics of Applied Statistics, CRC Press; ISBN: 0412070111.

J. Faraway (2004). Linear Models with R, CRC Press; ISBN: 1584884258.

Other References:

S. Chatterjee, A. Hadi and B. Price (2006). Regression Analysis By Example. 4th Edition. Wiley.

Ryan, Thomas P. (1997). Modern Regression Methods. Wiley. (A list of corrections is here.)

Draper, Norman R. and Harry Smith (1998). Applied regression analysis. 3rd ed. Wiley.

B. Ripley and W. Venables (1999). Modern Applied Statistics with S-PLUS (Statistics and Computing) . Springer-Verlag.
R. Heiberger and B. Holland (2004). Statistical Analysis and Data Display; An Intermediate Course with Examples in S-PLUS, R, and SAS. Springer.

Grades:

Homework assignments and group discussion will be counted 50% towards the final grade.
A final project will be counted 50% towards the final grade.

Basic Rule: No Late Homework. The minimal score to pass the course is 60 out of 100 scale.

Official Final Exam Date: Dec 12, 2006