Academic Programs Catalog

College of Natural Science

Department of Statistics and Probability

Lyudmila Sakhanenko, Chairperson

Statistics, as a discipline, drives data science, and provides systematic ways for scholars from all fields to collect, summarize, model, and interpreting the data, basing their decisions on these analyses and their associated computational methods. Probability theory is a branch of mathematics used to develop and analyze various aspects of statistical models guided by practical aspects of computation and scientific interpretability. In the past 20 years, statistics and probability enabled great strides to be made in the physical, biological, social, and agricultural sciences, and in engineering and business. Statistics and probability are also areas of theoretical and basic methodological research, as self-standing intellectual endeavors which are part of the mathematical and computational sciences.


Undergraduate Programs

The first two years of an undergraduate program in statistics stress development of a solid background in two areas, basic mathematics and computers. The rest of the student’s program involves a mixture of work selected from statistics, mathematics, and computer programming, and possibly one or more fields of application. Statistics majors who plan to do graduate work should include advanced calculus in their undergraduate programs.  The department also offers courses for actuarial science majors housed in the Department of Mathematics.

 


Statistics

Requirements for the Bachelor of Science or Bachelor of Arts Degree in Statistics

  1. The University requirements for bachelor's degrees as described in the Undergraduate Education section of this catalog; 120 credits, including general elective credits are required for the Bachelor of Science or Bachelor of Arts degree in Statistics.

    The University's Tier II writing requirement for the Statistics major is met by completing Statistics and Probability 481.  That course is referenced in item 3. below.

    Students who are enrolled in the College of Natural Science may complete the alternative track to Integrative Studies in Biological and Physical Sciences that is described in item 1. under the heading Graduation Requirements in the College statement.  Certain courses referenced in requirement 3. below may be used to satisfy the alternative track.
  2. The requirements of the College of Natural Science for the Bachelor of Science degree or Bachelor of Arts degree.

    The credits earned in certain courses referenced in requirement 3. below may be counted toward College requirements as appropriate.
  3. The following requirements for the major:
                   
    a. The following courses (19 to 23 credits):
    (1) One of the following courses (3 or 4 credits):
    LB 118 Calculus I 4
    MTH 132 Calculus I 3
    MTH 152H Honors Calculus I 3
    (2) One of the following courses (4 credits):
    LB 119 Calculus II 4
    MTH 133 Calculus II 4
    MTH 153H Honors Calculus II 4
    (3) One of the following course (4 credits):
    LB 220 Calculus III 4
    MTH 234 Multivariable Calculus 4
    MTH 254H Honors Multivariable Calculus 4
    (4) One of the following groups of courses (4 to 7 credits):
    (a) MTH 299 Transitions 4
    MTH 309 Linear Algebra I 3
    (b) MTH 299 Transitions 4
    MTH 314 Matrix Algebra with Applications 3
    (c) MTH 317H Honors Linear Algebra 4
    (5) One of the following courses (4 credits):
    CMSE 201 Computational Modeling and Data Analysis I 4
    CSE 231 Introduction to Programming I 4
    b. The following courses (10 credits):
    (1) The following course (4 credit):
    STT 180 Introduction to Data Science 4
    (2) One of the following courses (3 credits):
    STT  441 Probability and Statistics I: Probability 3
    STT  861 Theory of Probability and Statistics I 3
    (3) One of the following courses (3 credits):
    STT 442 Probability and Statistics II: Statistics 3
    STT 862 Theory of Probability and Statistics II 3
    c. The following capstone course (3 credits):
    STT 481 Capstone in Statistics (W) 3
    d. Three of the following courses (9 or 10 credits):
    EC 821A Cross Section and Panel Data Econometrics I 3
    EC 821B Cross Section and Panel Data Econometrics II 3
    EC 822A Time Series Econometrics I 3
    EC 822B Time Series Econometrics II 3
    STT 422 Statistics II 3
    STT 455 Actuarial Models I 3
    STT 456 Actuarial Models II 3
    STT 459 Construction and Evaluation of Actuarial Models 3
    STT 461 Computations in Probability and Statistics 3
    STT 464 Statistics for Biologists 3
    STT 465 Bayesian Statistical Methods 3
    STT 801 Design of Experiments 3
    STT 802 Statistical Computation 3
    STT 814 Advanced Statistics for Biologists 4
    STT 825 Sample Surveys 3
    STT 843 Multivariate Analysis 3
    STT 844 Time Series Analysis 3
    STT 847 Analysis of Survival Data 3
    STT 855 Statistical Genetics 3
    STT 863 Statistical Methods I 3
    STT 864 Statistical Methods II 3
    STT 886 Stochastic Processes and Applications 3
    STT 888 Stochastic Models in Finance 3
    Not more than two courses may be chosen from STT 455, 456, or 459.
    e. Electives chosen from any combination of the following, approved by the student's academic advisor (6 credits):
    (1) Courses from item d. not used to fulfill that requirement with the exception of STT 455, 456, or 459;
    (2) MTH 235 or any 300-level or higher MTH course;
    (3) CSE 232 or 260 or any 300-level or higher CSE course; or CMSE 381 or any 400-level or higher CMSE course;
    (4) 300-400 level courses in an area of application of statistics and probability.


Quantitative Risk Analytics

The Bachelor of Science degree in Quantitative Risk Analytics provides students the quantitative skills necessary for employment in the insurance and risk industry, including a mathematical treatment of probability and statistics, interest-rate theory and financial mathematics, predictive analytics and other data science tools, and insurance operations.

Admission

To be considered for admission to the major, the student must have:

  1. a cumulative grade-point average of at least 3.0 in all courses taken at MSU.
  2. a minimum grade-point average of 3.0 in MTH 132, MTH 133, and MTH 234 or equivalent courses.
  3. a minimum average of 3.0 in the grades in MTH 360 and STT 441.
Students who declare the major in quantitative risk analytics are automatically reviewed at the end of every semester and are either admitted or informed of their progress. Students must be admitted to a degree-granting college at the time they have completed 56 credits. Those who do not meet the criteria may consider a major in either Mathematics or in Statistics and Probability.

Requirements for the Bachelor of Science Degree in Quantitative Risk Analytics
  1. The University requirements for bachelor's degrees as described in the Undergraduate Education section of this catalog; 120 credits, including general elective credits, are required for the Bachelor of Science degree in Quantitative Risk Analytics.

    The University's Tier II writing requirement for the Quantitative Risk Analytics major is met by completing Statistics and Probability 467.  That course is referenced in item 3. below. 

    Students who are enrolled in the College of Natural Science may complete the alternative track to Integrative Studies in Biological and Physical Sciences that is described in item 1. under the heading Graduation Requirements in the College statement.  Certain courses referenced in requirement 3. below may be used to satisfy the alternative track.
  2. The requirements of the College of Natural Science for the Bachelor of Science degree. The credits earned in certain courses referenced in requirement 3. below may be counted toward College requirements as appropriate.
  3. The following requirements for the major:
    a. One course of at least 3 credits in biological science, entomology, microbiology, physiology, plant biology, or integrative biology as approved by the student’s academic advisor.
    b. One of the following groups of courses (8 to 10 credits):
    (1) CEM  141 General Chemistry  4
    CEM 142 General and Inorganic Chemistry 3
    CEM  161 Chemistry Laboratory I  1
    (2) CEM 151 General and Descriptive Chemistry 4
    CEM 152 Principles of Chemistry 3
    CEM 161 Chemistry Laboratory I 1
    (3) CEM 181H Honors Chemistry I 4
    CEM 182H Honors Chemistry II 4
    CEM 185H Honors Chemistry Laboratory I 2
    (4) LB 171 Principles of Chemistry I 4
    LB 171L Introductory Chemistry Laboratory I 1
    LB 172 Principles of Chemistry II 3
    c. One of the following croups of courses (8 credits):
    (1) PHY 183 Physics for Scientists and Engineers I 4
    PHY 184 Physics for Scientists and Engineers II 4
    (2) PHY 193H Honors Physics I – Mechanics 4
    PHY 294H Honors Physics II – Electromagnetism 4
    (3) LB 273 Physics I 4
    LB 274 Physics II 4
    d. One of the following groups of courses (11 or 12 credits):
    (1) MTH  132 Calculus I  3
    MTH 133 Calculus II 4
    MTH 234 Multivariable Calculus 4
    (2) LB 118 Calculus I 4
    LB 119 Calculus II 4
    LB 220 Calculus III 4
    (3) MTH 152H Honors Calculus I 3
    MTH 153H Honors Calculus II 4
    MTH 254H Honors Multivariable Calculus 4
    e. One of the following courses (3 credits):
    MTH 235 Differential Equations 3
    MTH 340 Ordinary Differential Equations I 3
    MTH 347H Honors Ordinary Differential Equations 3
    f. One of the following groups of courses (4 to 7 credits):
    (1) MTH 299 Transitions 4
    MTH 309 Linear Algebra I 3
    (2) MTH 317H Honors Linear Algebra 4
    g. All of the following courses (15 credits):
    MTH 360 Theory of Mathematical Interest 3
    MTH 361 Financial Mathematics for Actuaries I 3
    MTH 457 Introduction to Financial Mathematics 3
    STT 441 Probability and Statistics I: Probability 3
    STT 442 Probability and Statistics II: Statistics 3
    h. Both of the following courses (6 credits):
    MTH 468 Predictive Analytics 3
    STT 467 Insurance Operations 3
    i. All of the following courses (19 credits):
    ACC 230 Survey of Accounting Concepts 3
    CSE 231 Introduction to Programming I 4
    EC 201 Introduction to Microeconomics 3
    EC 202 Introduction to Macroeconomics 3
    FI 311 Financial Management 3
    FI 321 Theory of Investments 3

 

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.