Statistics 325/425

Data Analysis and Linear Models

Syllabus, Fall 2011

Classes: 2:45-4:00 pm Tuesday and Thursday at Yost 101.

Instructor: Professor Jiayang Sun, Yost 326, 368-0630, jsun at case edu
Office Hours: 4:00-5:00pm Tuesday (subject to change).

Teaching Assistant: Blake Bankwitz
Office Hrs: MWF 1-3pm @Yost 339, 216-368-2135 (office), 313-303-2141 (cell)
Other TA's hours: http://stat.case.edu/tutor-schedule.pdf @ Yost 329 (to be updated)

Lab Administrator:
Office Hrs: M 3-5 and T 4-5 (Joe), W 3:15-4:15 (Greg) 4-5 (Joe), Th 4-5 and F 3-5 (Greg)
at Yost 335, 368-0417
e-mail: help at stat case edu or stats-help at case edu

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 (read a news report on R from New York Times). 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 class such as STAT207/208, or STAT 244 (that covers estimation and hypothesis tests), or STAT 312, or Stat 346, or one of EPBI 431/481.

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 (1997). 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 exam will be counted 50% towards the final grade.
Rule: No Late Homework. The minimal score to pass the course is 60 out of 100 scale.
Final Exam Time: 12:30-3:30pm, Dec 13, 2011 (Tuesday)
Class Webpage: sun.case.edu/~jiayang/425.html