Course Homepage: Spring 2007   (Past Pages: Spring 2004 )

Usually Offered: Spring and Summer Semesters

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.

Supplementary Material: Ten supplements to the textbook are available for download in .pdf format:

    Section 7.7 - More on Correlation
    Section 7.8 - Transformation of Variables
    Section 8.3 - Type I and Type III Sum of Squares
    Section 8.8 - More on Variable Selection
    Section 8.9 - More on Outlier Diagnostics
    Section 6.4 - The Modified Levene Test
    Section 6.5 - Contrasts and Multiple Comparisons
    Section 9.3 - Two-way ANOVA Formulas
    Section 10.2 - Interpreting Random Effects Output
    Section 11.7 - Estimation and Inference for Logistic Regression

Help in using SAS can be found on the SAS Templates page. This page is designed to be used interactively and is probably too long to print out.

 

Topics Covered	Chapters	Time
Simple Linear Regression: least squares estimation, inferences for regression, the ANOVA table, the correlation coefficient, use of SAS	7	2.5 weeks
Multiple Linear Regression: inference for multiple regression, residual diagnostics, leverage and influence, transformations, multicolinearity, model selection	8	3 weeks
One-way Analysis of Variance (ANOVA): traditional analysis of variance notation, using linear regression, multiple comparisons, contrasts, assumption checking	6	2.5weeks
ANOVA for Standard Experimental Designs: two-way ANOVA, higher order factorial designs, unbalanced data, incomplete data, randomized block designs, random effects	9-11	3 weeks
Other Models: Analysis of Covariance, and selections from: nested designs, repeated measures*, nonlinear regression, logistic regression, proportional hazards*	11	2 weeks
* indicates topic not covered in the text

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: David Hitchcock, Brian Habing
(Last Updated: July 11, 2008)