704—Data Analysis I (3) (Prereq or coreq: STAT 712) Primarily for graduate students in statistics and the mathematical sciences. Probability concepts, inferences for normal parameters, regression, correlation, use of computer statistical packages.

Sample Course Homepage: Recent Semester, Another Recent Semester

Usually Offered: Fall Semester

Purpose: To provide an overview of normal-model inference and a strong background in regression modeling.

Current Textbooks:

Applied Linear Statistical Models , (5th edition), Kutner, Nachtsheim, Neter, and Li. McGraw-Hill/Irwin, 2005.

 

Topics Covered	Chapters	Time
Random Variables, Expected Value, Variance, and Covariance  Normal distribution and other sampling distributions	Notes	1 week
Single-sample models, t-based inference, and nonparametric alternatives	Notes	1 week
Simple Linear Regression and Correlation	KNNL Chs 1-2	2 weeks
Multiple Regression	KNNL Chs 6-11	5 weeks
Nonlinear Regression	KNNL Ch 13	1 week
Logistic Regression and Count Regression	KNNL Ch 14	2 weeks
Nonparametric Regression	Notes	1 week

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