625.663.8VL - Multivariate Statistics and Stochastic Analysis

Course Structure

The course materials are divided into modules which can be accessed by clicking Modules on the course menu. A module will have several sections including the overview, content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Most modules run for a period of seven (7) days, exceptions are noted in the Course Outline. You should regularly check the Calendar and Announcements for assignment due dates.

Course Topics

Multivariate analysis arises with observations of more than one variable when there is some probabilistic linkage

between the variables. In practice, most data collected by researchers in virtually all disciplines are multivariate in

nature. In some cases, it might make sense to isolate each variable and study it separately. In most cases,

however, the variables are interrelated in such a way that analyzing the variables in isolation may result in failure

to uncover critical patterns in the data. Multivariate data analysis consists of methods that can be used to study

several variables at the same time so that the full structure of the data can be observed and key properties can be

identified. This course covers estimation, hypothesis exams, and distributions for multivariate mean vectors and

covariance matrices. We also cover popular multivariate data analysis methods including multivariate data

visualization, maximum likelihood, principal components analysis, multiple comparisons exams, multidimensional

scaling, cluster analysis, discriminant analysis and multivariate analysis of variance, multiple regression and

canonical correlation, and analysis of repeated measures data.

Course Goals

This course introduces statistical methods for analysis and interpretation of multivariate data. Students will gain

insights on how the methods are developed and gain ability to analyze multivariate data with appropriate

methods.

Textbooks

Applied Multivariate Statistical Analysis (Classic Version), 6th Edition, 2019

Author: Richard A. Johnson, Dean W. Wichern

ISBN 13: 978-0-13-499539-7

ISBN 10: 0-13-499539-2

MBS Direct SKU #: 2148993

Publisher: Pearson

Required Software

There is no required software to purchase. You are free to use any mathematical or statistical software, such as

Student Coursework Requirements

Preparation and Participation (10 points)

You are responsible for carefully reading all assigned material. The majority of readings are from the course text.

Additional reading may be assigned to supplement text readings. Class participation includes virtual live session

discussion, Forum, or by-email discussion. You are encouraged to work with classmates for discussion.

Assignments (25 points)

Assignments will include quantitative problem sets for analytical derivation or statistical analyses. Include a cover

sheet with your name and assignment identifier. Also include your name and a page number indicator (i.e., page x

of y) on each page of your submissions. Each problem should have the problem statement, assumptions,

computations if applicable, and conclusions/discussion delineated. All Figures and Tables should be captioned

and labeled appropriately.

You are expected to work on all assignments independently.

All assignments are due according to the dates in the Calendar.

Late submissions will be reduced by 50% of the total score for that assignment for each week late (no exceptions

without prior coordination with the instructor).

Quantitative assignments are evaluated by the following grading elements:

1. Each part of problem is answered.
2. Assumptions are clearly stated.
3. Intermediate derivations and calculations are provided in detail.
4. Answer is technically correct and is clearly indicated.

Exams (Exam 1: 30 points, Exam 2: 35 points)

Exam 1 will be given in Week 7 and Exam 2 in Week 14. You will have seven days to complete the exams and

they will be due by the time specified on the Calendar. You may use the course text to complete the exams. You

are expected to work on all the exams independently.

The exams are evaluated by the following grading elements:

1. Each part of problem is answered.
2. Assumptions are clearly stated.
3. Intermediate derivations and calculations are provided.
4. Answer is technically correct and is clearly indicated.

Grading Policy

EP uses a +/- grading system (see “Grading System”, Graduate Programs catalog, p. 10).

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.