Time: Monday, Wednesday, Friday at 10:00 a.m. - 10:50 a.m.
Location: Taft Hall 301
Instructor: Jie Yang
Office: SEO 513
Phone: (312) 413-3748
E-Mail: jyang06 AT math DOT uic DOT edu
Office Hours: Monday, Wednesday, Friday at 12:00 p.m. - 1:00 p.m.
Textbook: Richard A. Johnson, Dean W. Wichern,
Applied Multivariate Statistical Analysis, Pearson Prentice Hall, 6th edition, 2007
Reference Books:
Homework:
Turn in every Friday before class;
half of the grade counts for completeness;
half of the grade counts for correctness of one selected problem
Midterms: February 15th (Friday), and March 20th (Wednesday), 10:00 a.m. - 10:50 a.m.
Final Exam: May 10th (Friday), 10:30 a.m. - 12:30 p.m.
Grading: Homework 10%, midterms 25% each, final exam 40%
Grading Scale: 90% A , 80% B , 70% C , 60% D
Format of All Exams: Each exam is based on the homework and the examples discussed in class. The last class session before each exam is a review session. Please prepare any questions that you may have.
No makeup exam will be given without a valid excuse.
| WEEK | SECTIONS | BRIEF DESCRIPTION |
| 01/14 - 01/18 | 1.1, 1.2, 1.3; 2.1, 2.2, 2.3; 2.5, 2.6 | Aspects of Multivariate Analysis; Some Basics of Matrix and Vector Algebra, Positive Definite Matrices; Random Vectors and Matrices, Mean Vectors and Covariance Matrices |
| 01/21 - 01/25 | Holiday; 3.3, 3.5, 3.6; 4.1, 4.2 | Sample Geometry and Random Sampling; Multivariate Normal Density and Its Properties |
| 01/28 - 02/01 | 4.3; 4.4, 4.5; 4.6 | Sampling from a Multivariate Normal Distribution and Maximum Likelihood Estimation; Sampling Distribution of Xbar and S, Large-Sample Behavior of Xbar and S; Assessing the Assumption of Normality |
| 02/04 - 02/08 | 5.1, 5.2; 5.3; 5.4 | Plausibility of mu0 as a Value for a Normal Population Mean; Hotelling's T^2 and Likelihood Ratio Tests; Confidence Regions and Simultaneous Comparisons |
| 02/11 - 02/15 | Review; 5.5; Midterm-1 exam; | Large Sample Inferences about a Population Mean Vector |
| 02/18 - 02/22 | 6.1, 6.2; 6.3; 6.4 | Paired Comparisons and a Repeated Measures Design; Comparing Mean Vectors from Two Populations; Comparing Several Multivariate Population Means |
| 02/25 - 03/01 | 6.5, 6.6; 6.7; 7.1, 7.2, 7.3 | Simultaneous Confidence Intervals for Treatment Effects, Testing for Equality of Covariance Matrices; Two-Way Multivariate Analysis of Variance; Classical Linear Regression Model, Least Squares Estimation |
| 03/04 - 03/08 | 7.4; 7.6; 7.7 | Inferences about the Regression Model; Model Checking and Other Aspects of Regression; Multivariate Multiple Regression |
| 03/11 - 03/15 | 7.7; 7A; 7.10 | Multivariate Multiple Regression; Distribution of the Likelihood Ratio; Multiple Regression Models with Time Dependent Errors |
| 03/18 - 03/22 | Review; Midterm-2 exam; 8.1, 8.2 | Population Principal Components |
| 04/01 - 04/05 | 8.2; 8.3; 8.5, 8A | Population Principal Components; Summarizing Sample Variation by Principal Components; Large Sample Inferences, Geometry of Sample Principal Component Approximation |
| 04/08 - 04/12 | 9.1, 9.2; 9.3; 9.3 | Orthogonal Factor Model; Methods of Estimation; Methods of Estimation |
| 04/15 - 04/19 | 10.1, 10.2; 10.3; 10.4 | Canonical Variates and Canonical Correlations; Interpreting the Population Canonical Variables; Sample Canonical Variates and Sample Canonical Correlations |
| 04/22 - 04/26 | 11.1, 11.2; 11.3; 11.4 | Introduction, Separation and Classification for Two Populations; Classification with Two Multivariate Normal Populations; Evaluating Classification Functions |
| 04/29 - 05/03 | 11.6, 11.7; Review; Review | Fisher's Method for Discriminating, Logistic Regression and Classification |
| 05/06 - 05/10 | Exam week | (Final exam) |