UNLV Department of Mathematical Sciences

STA 715 Applied Multivariate Analysis

Teaching & Class Materials

Welcome to the course homepage for STA715. If you are a student in this class you should check this site frequently for updated information and announcement.

graduate Program: (MS, PhD)

Related Course:  [STA761]   [STA762]

I. Outline of the Course


Instructor: Hokwon A. Cho, Ph.D., Associate Professor, Office: CDC 1008 (Building #10, Room 1008), Office phone: 895-0393 (Math. Sci. dept. office: 895-3567), E-mail: cho@unlv.nevada.edu.

Class Time and Location: Tu, Th 11:30am - 12:45pm, BEH 221.

Office Hours: Tu & Th: 2:30pm-4:30pm or by appointment.

Textbook: Applied Multivariate Statistical Analysis, 6th Edition by R. Johnson and D. Wichern. Prentice Hall, New Jersey.

Description of the Course:   The main goal of this course is to provide the conceptual foundations (theory) and their applications of the multivariate statistical methods. Thus, the emphasis will be on understanding the infrastructure of methodologies and computational techniques including data analysis (using statistical software/packages). Several major topics covering will be


1.       Introduction to Basic Concepts and Background - Multivariate Data, Random Vectors, Graphical Methods, Basic Matrix Algebra, Expectation, Sample Geometry and Random Sampling.

2.       Theory of Multivariate Normal Distribution - Multivariate Normal, Sampling Distributions of Sample Mean and Sample Variance, MLE, Asymptotics.

3.       Inference on Mean Vectors - Hotelling's T² statistic and Wishart distribution, Inferences on Mean Vector and Likelihood Ratio Tests.

4.       Analysis of Covariance Structures – Linear Regression Models, Principal Components, Factor Analysis and Canonical Correlation Analysis.

5.       Classification and Grouping Techniques - Classification, Discrimination Analysis, Clustering, Multidimensional Scaling, and some Selected Topics if time permitted.


Homework: There will be roughly weekly assignments will be given in class (on a Tuesday) and expected to turn in on time. Some of them will be discussed in class.


Grading: The course grade is evaluated based upon the following components: Homework & assignments - 20%, Two tests (in class) - 25% each, Final Exam - 30%.


Exams: There will be two midterm exams most likely on 6th and 11th week. The final exam is scheduled according to the university calendars and schedules.


University Academic Policies on the Academic Misconduct, Copyright, Disability Resources Center (DRC), Tutoring, Writing Center, and Religious Holidays: click the next è University Academic Policies.


II. Lecture, Homework Schedule & Handout


Ÿ To see the list of reference and further reading, click next è [Reference & Further Reading]

Ÿ To see the lecture and homework schedule, click next è [Lecture & HW schedule]


The following item will be distributed in the class as lectures proceed (and rarely posted).

§   Homework & Solutions


III. Bulletin Board

Last updated: 10:00 AM  Mon.  Aug. 22, 2016

All exams/quizzes are closed book and notes.


1.    Welcome to STA 715.

2.    Lecture schedule will be distributed in class.


IV. Handouts, Data Sets & Other Resources



§  [MINITAB Quick Reference] [Minitab Basic 1] [Minitab Basic 2]


Data Sets: You can download all data sets used in the text from the textbook website.

Table1-5 (Air-Polution data)

Table1-8 (Mineral data)

Table1-9 (Track data)

Table3-2 (Snow data)



Table4-1 (Radiation data)

Table4-3 (Stiffness data)

Table4-6 (Profile Data)

Table5-2 (College Test data)

Table5-11 (Lumber data)

Table6-19 (Anaconda data)



Table8-5 (Census-tract data)






o    Statistical Software & Language:  | R | S-Plus | Minitab | SAS/JMP | SPSS | STATA | BMDP |

o    Search Journal Articles on Web:  |JSTOR | MathSciNet | Ingenta | CIS  | Thomson | Wikipedia |


Ø  Journals:   | Statistics | Probability | Related Journals | Mathematics |

Ø  Societies:   | IMS | ASA | IMS BulletinSIAM | AMS | MAA |                    è More Link?


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© 2006-2017  Hokwon Cho.