Syllabus Rev. 8/27/01

Prerequisite: STA 3163

Terms offered: Spring

Textbook: An Introduction to Statistical Methods and Data Analysis, 5th edition, by R. Lyman Ott and Michael Longnecker, 2001. Duxbury.

Note: Statistical software packages will be used in this course..

Topics:

1. Linear Regression and Correlation. Introduction. The method of least squares. Statistical inference and prediction. Examination of lack-of-fit. Correlation.

2. Multiple Regression and the General Linear Model. Introduction. The general linear model. Least squares solution and the normal equations. Statistical inference about one or more parameters.

5. Analysis of Variance. Introduction. The one-way analysis of variance. Hartley's test of homogeneity of variances. The Kruskal-Wallis test as a non-parametric alternative.

6. Multiple Comparison Procedures. Linear contrasts. Error rates. Fisher's LSD, Tukey's W procedure, Student-Newman-Keuls procedure, and other methods.

7. Basic Experimental Designs. The completely randomized design and the randomized complete block design. Two-factor factorial experiments fitted into a CRD.

8. Analysis of Covariance. Introduction. The completely randomized design with one covariate. The extrapolation problem.