George Mason University
School of Information Technology and Engineering
Department of Applied and Engineering Statistics


STAT 535: Analysis of Experimental Data

Fall Semester, 2005
Thursdays from 7:20 to 10:00 PM (starting Sep. 1, with other dates given below)

Location: room 205 of Krug Hall

Instructor: Clifton D. Sutton

Contact Information (phone, fax, e-mail, etc.)
Office Hours: 6:00-7:00 & 10:00-10:30 PM on class nights (more information)


Texts:


Software:

I will explain how the SPSS Graduate Pack can be used to perform a lot of the procedures covered in the course. (You are free to use other software as long as you obtain the correct answers, but you'll be on your own with regard to using anything other than SPSS Graduate Pack. I strongly recommend that you use SPSS since it's what I'll teach you how to use.) The SPSS Graduate Pack may be purchased at Patriot Computers in the Johnson Center (near the bookstore). (I encourage you to try to purchase it as soon as possible, since if they run out, they may not quickly order more unless there is a demand for it. Also, make sure that you buy the correct version for your computer --- the store tends to mix the Mac stuff in with the regular PC stuff.) Alternatively, if you go to the e-academy web site and click on SOFTWARE, you can click further to find that you can rent the SPSS Graduate Pack for 6 months for $79.99.


Prerequisite: STAT 250 or IT 250 or equivalent (e.g., BIOL 312)


Description:

Statistical methods for the analysis of experimental data, including ANOVA and regression. After a brief review of elementary probability, both parametric and nonparametric inference methods appropriate for a variety of experimental designs are presented, and the use of appropriate statistical software is taught.

(Approximate) Class-by-Class Content:

[1] Sep. 1:
Introduction to the analysis of data from designed experiments; Elementary probability theory ( Ch. 1 & Ch. 3 (through p. 92) of S&W)
[2] Sep. 8:
More probability; Binomial distributions ( Ch. 3 (from p. 93) of S&W)
[3] Sep. 15:
Normal distributions; Descriptive statistics; Introduction to SPSS ( Ch. 2 & Ch. 4 of S&W)
[4] Sep. 22:
Sampling distributions; Confidence intervals ( Ch. 5 & Ch. 6 of S&W)
[5] Sep. 29:
Hypothesis testing; Statistical methods for two-sample experiments ( Ch. 7 of S&W)
[6] Oct. 6:
Basics of experimental design ( Ch. 8 of S&W)
[7] Oct. 13:
Statistical methods for matched-pairs experiments ( Ch. 9 of S&W)
[8] Oct. 20:
One-way ANOVA; Multiple comparisons; Related nonparametric methods ( Ch. 11 (except Sec. 11.6) of S&W & (parts of) Ch. 1 of G&H)
[9] Oct. 27:
Simple linear regression; Correlation ( Ch. 12 of S&W & (parts of) Ch. 2 of G&H) --- midterm exam distributed
[10] Nov. 3:
Introduction to multiple regression ( (parts of) Ch. 4 of G&H) --- midterm exam due
[11] Nov. 10:
More on multiple regression ( (parts of) Ch. 4 of G&H)
[12] Nov. 17:
Analysis of covariance (ANCOVA) ( (parts of) Ch. 4 & Ch. 6 of G&H)
[**] Nov. 24:
No class (due to Thanksgiving break)
[13] Dec. 1:
More on ANOVA (two-way ANOVA, random effects, other designs) ( Sec. 11.6 of S&W & (parts of) Ch. 12 of G&H)
[14] Dec. 8:
Categorical data analysis; Summary and brief mention of other topics ( Ch. 10 & Ch. 13 of S&W & (parts of) Ch. 13 & Ch. 14 of G&H)
[**] Dec. 15:
Final Exam (note: exam period is from 7:30 to 10:15 PM)

Grading:


Additional Comments: