Overview

COURSES
  • Required Courses

    The M.S. degree in Applied Statistics requires 30 hours, 12 of which are electives. There are five different tracks within this degree to allow different specializations. These include: Traditional, Biostatistics, Actuarial Science, Data Mining, Quality and Six Sigma. There are six required courses and four elective courses common to all five tracks of study.

    The electives may be earned in additional coursework with the approval of a faculty advisor. The program of related courses may vary from student to student and depends on the student's interests and academic background. When most of the coursework is completed, the student must pass a written comprehensive examination.


    ST 552
    Applied Regression Analysis
    ST 553
    Applied Multivariate Analysis
    ST 554
    Mathematical Statistics I
    ST 555
    Mathematical Statistics II
    ST 560
    Statistical Methods
    ST 561
    Applied Design of Experiments
  • Statistics Electives
    ST 521
    Statistical Data Management
    ST 522
    Advanced Statistical Data Management
    ST 531
    Knowledge Discovery & Data Mining I
    ST 532
    Advanced Data Mining II
    ST 565
    Sampling Techniques 
    ST 570
    Time Series Analysis
    ST 575
    Statistical Quality Control
    ST 591
    Independent Study
    ST 597
    Special Topics
    ST 603
    Advanced Inference
    ST 610
    Linear Models
    ST 635
    Nonparametric Statistics 
    ST 640
    Statistical Computing
    ST 698
    Statistical Consulting
  • Traditional Track
    ST 535
    Nonparametric Statistics
    ST 575
    Statistical Quality Control

    Six hours of approved electives are also required.

  • Biostatistics Track
    ST 521
    Statistical Data Management
    ST 522
    Advanced Data Management
    CHS 520
    Basic Epidemiology
    CHS 625
    Advanced Epidemiology
  • Actuarial Science Track
    ST 521
    Statistical Data Management
    ST 535
    Nonparametric Statistics
    FI 443
    Property & Liability Insurance
    FI 444
    Life & Health Insurance
  • Data Mining Track
    ST 521
    Statistical Data Management
    ST 522
    Advanced Data Management
    ST 531
    Knowledge Discovery & Data Mining I
    ST 532
    Advanced Data Mining II
  • Quality and Six Sigma Track
    ST 575
    Statistical Quality Control
    IE 521
    Reliability, Maintainability & Total Productive Maintenance
    IE 622
    Quality Engineering

    Three hours of approved Statistics electives are also required.

faculty
and staff
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Contacts
Program Coordinator
Dr. Mike Adams 205-348-8911
371 Alston Hall
Box 870226
Contact
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