Academic Programs Catalog

College of Natural Science

Graduate Study

The Department of Statistics and Probability offers three majors that lead to master’s degrees: applied statistics, data science, and statistics.  The department also offers a major in statistics that leads to the Doctor of Philosophy degree.

Each of the master’s and doctoral degree programs is described below. For more detailed information on degree requirements please visit the department website, www.stt.msu.edu.


Applied Statistics - Master of Science

The goal of the master's degree program in applied statistics is to provide students with a broad understanding of the proper application of statistical methodology and with experience in using computers effectively for statistical analysis. The student may emphasize either theoretical or applied material. Special emphasis is placed on the concerns that an applied statistician must address in dealing with practical problems.

In addition to meeting the requirements of the university and of the College of Natural Science, students must meet the requirements specified below.

Admission

To be admitted to the master's degree program in applied statistics, the applicant should have a background in calculus equivalent to MTH 132, 133, and 234 at Michigan State University, a background in linear algebra equivalent to MTH 309 at Michigan State University, and at least one post-calculus –level course in statistics or probability. The overall grade-point average in these courses should be at least 3.0.

Requirements for the Master of Science Degree in Applied Statistics

The program is available only under Plan B (without thesis). An academic advisor coordinates the student's program of study, which must be approved by the chairperson of the department.

The student must:

               
1. Complete either a. or b.      
  a. All of the following courses (15 credits):  
    STT 441 Probability and Statistics I: Probability

3
    STT 442 Probability and Statistics II: Statistics

3
    STT 801 Design of Experiments

3
    STT 802 Statistical Computation

3
    STT 863 Statistical Methods I

3
  b. All of the following courses (15 credits):  
    STT 801 Design of Experiments 3
    STT 802 Statistical Computation 3
    STT 861 Theory of Probability and Statistics I 3
    STT 862 Theory of Probability and Statistics II 3
    STT 863 Statistical Methods I 3
2. Complete at least 9 additional credits in courses in the Department of Statistics and Probability at the 800-level or higher.  
3. Complete an additional 9 credits in courses in the Department of Statistics and Probability, the Department of Mathematics, or in a field of application of statistics and probability.  
4. Complete a final examination or evaluation.  


Data Science - Master of Science

The Master of Science degree in Data Science is designed to provide students with an interdisciplinary blend of statistics, computer science, and computational science and mathematics which provides the necessary training to assimilate, process, analyze, and interpret data from diverse sources.

Admission

To be considered for admission to the master’s degree, a student must:

  1. Have a four-year bachelor’s degree in a relevant quantitative discipline.
  2. Demonstrate sufficient quantitative preparation through work  or other relevant experiences.
In addition to meeting the requirements of the university and of the College of Natural Science, students must meet the requirements specified below.

Requirements for the Master of Science Degree in Data Science

A total of 30 credits is required for the degree under Plan B (without thesis). The student’s program of study must be approved by the student’s guidance committee and must meet the requirements specified below.
1. All of the following courses (18 credits):
CMSE 830 Foundations of Data Science 3
CMSE 831 Computational Optimization 3
CSE 482 Big Data Analysis 3
CSE 881 Data Mining 3
STT 810 Mathematical Statistics for Data Scientists 3
STT 811 Applied Statistical Modeling for Data Scientists 3
2. Complete 9 credits of elective courses from the following:
CMSE 402 Data Visualization Principles and Techniques 3
CMSE 822 Parallel Computing 3
CMSE 890 Selected Topics in Computational Mathematics, Science, and Engineering 1 to 4
CSE 802 Pattern Recognition and Analysis 3
CSE 830 Design and Theory of Algorithms 3
CSE 847 Machine Learning 3
STT 802 Statistical Computation 3
STT 812 Statistical Learning and Data Analysis 3
STT 873 Statistical Learning and Data Mining 3
STT 874 Introduction to Bayesian Analysis 3
STT 875 R Programming for Data Sciences 3
CMSE 890 must be approved by the student’s guidance committee.
Other courses may be available to fulfill this requirement with advisor approval.
3. Completion of a 3-credit capstone course involving an applied, industrial, or governmental data science project. Students may complete this requirement by enrollment in Computer Science and Engineering 890, Computational Mathematics, Science, and Engineering 890, or Statistics and Probability 890. The student’s topic area must be approved by the student’s guidance committee.
4. Completion of a final examination or evaluation.

Statistics - Master of Science

The goal of the master's degree program in statistics is to provide students with a sound foundation in probability, mathematical statistics, and statistical methodology. The student may emphasize either theoretical or applied material.

In addition to meeting the requirements of the university and of the College of Natural Science, students must meet the requirements specified below.

Admission

To be admitted to the master’s degree program in statistics, the applicant should have a background in calculus equivalent to Mathematics 132, 133, and 234, in linear algebra equivalent to Mathematics 309, and probability and statistics equivalent to Statistics and Probability 441 and 442 at MSU with an overall grade point average of 3.0 in this course work.

Requirements for the Master of Science Degree in Statistics

The program is available under either Plan A (with thesis) or Plan B (without thesis). An academic advisor coordinates the student's program of study, which must be approved by the chairperson of the department.

The student must complete:

  1. At least 30 credits in courses in the Department of Statistics and Probability, or in a related field including:
                 
  a. All of the following courses (12 credits):  
    STT 861 Theory of Probability and Statistics I 3
    STT 862 Theory of Probability and Statistics II 3
    STT 863 Applied Statistics Methods I 3
    STT 864 Applied Statistics Methods II 3
  b. Nine additional credits in STT courses at the 800-level or above as approved by the student’s academic advisor. At least 4 credits must be in STT 899 Master’s Thesis Research.  
  c. Nine additional credits in STT courses or courses in related fields as approved by the student’s academic advisor.  
  d. Completion of an oral examination in defense of the thesis, final examination or evaluation.  

Statistics - Doctor of Philosophy

The Doctor of Philosophy degree program with a major in statistics is designed for students who plan to pursue careers in university teaching and research or in industrial and government consulting and research.

In addition to meeting the requirements of the university and of the College of Natural Science, students must meet the requirements specified below.

Admission

A master’s level understanding of statistics and probability and a sound understanding of undergraduate-level real analysis are necessary for success in the doctoral program. Strong applicants with deficiencies in one of these areas will be considered for admission, and if accepted will be given the opportunity to learn the required material during their first year in the program. The Graduate Record Examination (GRE) General Test is required of all applicants.

Requirements for the Doctor of Philosophy Degree in Statistics

The program of study is developed by the guidance committee in consultation with the student. Students must be able to carry on significant original research in statistics or probability, as demonstrated in the dissertation, the student must also meet the requirements specified below:

  1. Complete Statistics and Probability 867, 868, 872, 881, and 882.
  2. Complete at least five additional courses from lists (a) and (b), with at least one course from a. and one from b.:
    a.    Advanced Probability: Statistics and Probability 961, 962, 964, 996.
    b.    Advanced Statistics: Statistics and Probability 873, 874, 951, 953, 997.
  3. Complete at least three additional elective courses offered at the 800-level or higher from any department. These courses must be approved by the student’s guidance committee.
  4. Pass two written preliminary examinations, the first covering Statistics and Probability 867, 868, and 872, and the second covering Statistics and Probability 881 and 882.