Title
Multivariate Statistical Analysis
Course Materials
R.A. Johnson and D.W. Wichern (2007). Applied Multivariate Statistical Analysis, 6th Ed., Pearson
Prentice-Hall, Upper Saddle River, NJ.
Course Description
STA 4702/5701 is an introductory course in statistics when responses are more than one characteristic or variable is observed on units (thus multivariate). We begin with a review of the relevant matrix theory/applications and common statistical distributions as well as the Multivariate Normal Distribution. Methods of inference regarding multivariate means will include: Hotelling’s T2, Multivariate Analysis of Variance (MANOVA), Multivariate Regression, and Repeated Measures (Growth Curves). Methods of inference regarding Covariance structure will include: Principal Components, Factor Analysis, and Canonical Correlation. Classification techniques will include: Discriminant Analysis and Cluster Analysis. Note that these methods (and the textbook) can be quite technical, and we will focus mostly on applications to various datasets to understand the methods.
Grading Scale
Exams will count 28% each, and Homework Assignments will count 4% each to the Final total of 100%.
- A 90+
- A- 89.99-87.5
- B+ 87.49-85
- B 84.99-80
- B- 79.99-75
- C+ 74.99-70
- C 69.99-65
- C- 64.99-60
- D 59.99-50
Attendance/Exam/Assignment Policies
While attendance is not taken, students are expected to attend lectures and participate in class. Make-up exams will only be considered with documented medical event or conference attendance (graduate students) and must be taken within 7 days of scheduled exam. Early exams will be given under no circumstances. Assignments are to be handed in during class on the date the assignment is due in paper format. Electronic submission of assignments will not be accepted. Turn off cell phones during classes. Students can bring 1 hand-written formula sheet (8.5”x11”) to exams, and any calculator without internet access.