Academic Information

The master’s in statistics requires 33 hours, (24 IGSDSP hours including STAT 537-538, STAT 563-564 and at least three more hours in a STAT courses). Up to nine hours of courses can be used to fulfill both doctoral degree and minor or master in statistics requirements. Some of the Level B hours may be obtained from certain Level A courses upon approval by the IGSDSP Executive Committee and the student’s home department.

Level A courses are introductory, graduate-level applied statistics courses. Level B courses are graduate-level applied statistics courses which have Level A (or equivalent) prerequisites. Some approved Level B courses Level B courses can be substituted for Level A courses. Please talk with your advisor about these options.

Curriculum

Doctoral Students Pursuing an M.S. in Statistics:

Doctoral students can earn a master’s in statistics by taking 33 hours of coursework, including 24 hours in approved IGSDSP courses.

STAT 537 – 538 (6 hrs)

STAT 563 – 564 (6 hrs)

3 hours from an additional Level B STAT courses

9 hours from any approved Level B courses

9 hours from technical courses in your concentration

No Comprehensive Exam Required (Must Receive A or B in Statistics 563 and 564)

Must Have IGSDSP Member on Committee

Of the required 24 hours of IGSDSP coursework, up to 9 hours can be taken from the department of the student’s primary major.

Doctoral Students Pursuing a Minor in Statistics:

For doctoral degree students, the minor in statistics requires 15 credit hours.

6 hours of approved Level A courses

9 hours of approved Level B courses

No Comprehensive Exam Required

Must Have IGSDSP Member on Committee

Up to 9 hours in approved IGSDSP courses can be taken from the department of the student’s primary major.

Master’s Students Pursuing a Minor in Statistics:

For master’s students, the minor in statistics requires 9 credit hours. Approved coursework taken through the department of the student’s primary major may be applied towards the master’s or minor requirements.

6 hours of approved Level A courses

3 hours of approved Level B courses

No Comprehensive Exam Required

Must Have IGSDSP Member on Committee

Up to 9 hours in approved IGSDSP courses can be taken from the department of the student’s primary major.

Level A courses are introductory, graduate-level applied statistics courses. Level B courses are graduate-level applied statistics courses that have Level A (or equivalent) prerequisites. Upon approval by the IGSDSP Executive Committee and the student’s home department, some of the Level B hours may be obtained from certain Level A courses.

Approved Courses

Level A – these courses are taken as a series of two:

  • STAT 537 and STAT 538 Statistics for Research I, II
  • Either PLSC 561 Statistics for Biological Research or STAT 537 and ANSC 571 Design and Analysis of Biological Research
  • POLS 512 and POLS 513 Quantitative Political Analysis I, II
  • SOWK 605 and SOWK 606 Analysis of Social Work Data I, II (College of Social Work only)
  • STAT 537 and SOWK 606 Analysis of Social Work Data II
  • IE 516 Statistical Methods in Industrial Engineering and STAT 538 Statistics for Research II
  • PSYC 521 and PSYC 522 Analysis of Variance for Social Sciences – Multiple Regression for Social Sciences
  • ANTH 504 Anthropological Statistics I and STAT 538 Statistics for Research II
  • EMS 577 and EMS 677 Statistics for Applied Fields I, II
  • PUBH 530 Biostatistics and STAT 538 Statistics for Research II
  • GEOG 515 Topics in Quantitative Geography and STAT 537 Statistics for Research I

Level B – Please select from the following courses to fulfill the remainder of your required IGSDSP courses according to your degree program as shown above (PhD with MS in Stats, PhD with minor in Stats, or MS/MA degree with minor in Stats):

Business Analytics and Statistics

  • STAT 563-564 (Required for MS in Statistics)
  • STAT 567 Analysis of Lifetime Data
  • STAT 573 Design of Experiments
  • STAT 575 Applied Time Series Communication and Information
  • STAT 577 Data Mining Methods and Applications
  • STAT 578 Categorical Data Analysis
  • STAT 579 Applied Multivariate Methods
  • STAT 583 Special Topics in Applied Statistics
  • STAT 593 Independent Study
  • BZAN 615 Statistical Learning
  • BZAN 620 Applied Optimization and Data Analysis
  • BZAN 640 Data Science From Business Research
  • BZAN 645 Machine Learning

Management

  • MGT 627 Structural Equation Models in Organizational Research

Economics

  • ECON 582 Elements of Econometrics I
  • ECON 583 Elements of Econometrics II
  • ECON 682 Advanced Microeconometrics
  • ECON 683 Time Series Econometrics

Communications

  • CCI 640 Advanced Communication and Information Research Methods: Advanced Design and Analysis

Industrial Engineering

  • IE 542 Design of Experiments for Engineering Managers
  • MSE 576 Machine Learning for Materials
  • CEE 559 TRANSPORTATION SAFETY
  • IE 565 Applied Data Science
  • IE 603 Advanced Design and Analysis of Experiments
  • IE 607 Stochastic Processes

Computer Science

  • COSC 522 Machine Learning
  • COSC 525 Deep Learning
  • COSC 526 Data Mining
  • COSC 527 Biologically Inspired computing
  • COSC 530 Computer Systems Organization
  • COSC 545 Fundamentals of Digital Archeology
  • COSC 554 Markov Chains in Computer Science
  • COSC 557 Visualization
  • COSC 565 Databases and Scripting Languages

Electrical Engineering

  • ECE 504 Random Process Theory for Engineers
  • ECE 517 Reinforcement Learning

Nuclear Engineering

  • NE 579 Advanced Monitoring and Diagnostic Techniques
  • NE 585 Process System Reliability and Safety
  • NE 653 Theory of Information Processing

Anthropology

  • ANTH 604 Anthropological Statistics II

Math

  • MATH 423, 425 Probability I, Statistics
  • MATH 424 Stochastic Processes
  • MATH 523-524 Probability
  • MATH 525-526 Mathematical Statistics (Bayesian Statistics and Applications)
  • MATH 527 Stochastic Modeling
  • MATH 623 – 624 Advanced Probability

Geography

  • GEOG 510 Geographic Software Design
  • GEOG 517 Database Design for Spatial Data Science
  • GEOG 549 Topics in Geography of Transportation (which covers various spatial analysis methods for transportation and logistics problems)
  • GEOG 611 Seminar in Geographic Information Science
  • GEOG 649 Seminar in Geography of Transportation (which covers spatial optimization problems)

Political Science

  • POLS 515 Maximum Likelihood
  • POLS 516 Time Series
  • POLS 518 Bayesian Modelling in Political Science
  • POLS 610 Special Topics in Empirical Theory and Methodology

Psychology

  • PSYC 601 Hierarchical Linear Models
  • PSYC 622 Structural Equation Modeling
  • PSYC 607 Seminar in Applied Psychometrics

Sociology

  • SOCI 534 Advanced Sociological Analysis (topic-by-topic basis)
  • SOCI 631 Advanced Quantitative Methods

Educational Leadership and Policy

  • TPTE 595 An Introduction to Data Science Methods in Education (MS)
  • PUBH 635 Systematic Reviews and Meta-Analysis, Fall 2020
  • ESM 667 Advanced Topics: Multilevel Modeling
  • ESM 678 Statistics for Applied Fields III
  • ESM 680 Advanced Educational Measurement and Psychometrics
  • TPTE 695 An Introduction to Data Science Methods in Education (PhD)
  • HEAM 620

Public Health

  • PUBH 630 Advanced Biostatistics
  • PUBH 640 Advanced Epidemiology in Public Health

Animal Science

  • ANSC 572 Least Squares Analysis
  • AREC 524 Econometric Methods in Agricultural Economics
  • ANSC 675 Statistical Genomics
  • CEM 601 Advanced Epidemiology

 

Social Work

  • SOWK 665 Advanced Quantitative Research Methods: Applied Multilevel Modeling

Information Systems

  • CEM 601 Advanced Epidemiology
  • CEM 602 GIS and Geographical Epidemiology

Master's or Minor in Statistics