Master's Degree in Applied Statistics

Admission Requirements

The requirements for admission to the Graduate School are detailed in the UA Graduate Catalog. The candidate for a graduate degree in applied statistics is normally expected to have completed courses in mathematics equivalent to three semesters of undergraudate calculus, and to have a working knowedge of computer programming and linear or matrix algebra. The Graduate Record Examination (GRE) or the Graduate Management Aptitude Test (GMAT) is required of all applicants.

Degree Requirements

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 6 required courses common to all tracks and 4 elective courses. The requirements are listed below. The electives may be earned in additional coursework in statistics or related areas, 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 comprenehsive examination.

Statistics Electives

The following list of courses or related coursework approved by the applied statistics faculty can be used as suitable statistical electives.

ST 521 Statistical Data Management
ST 522 Advanced Statistical Data Management
ST 531 Knowledge Discovery and Data Mining I
ST 532 Advanced Data Mining II
ST 565 Sampling Techniques
ST 575 Statistical Quality Control
ST 570 Time Series Analysis

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

Tracks

Required courses all tracks

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

  • Traditional Track
    • ST 535, Nonparametric Statistics
    • ST 575, Statistical Quality Control
    • 6 hours Electives
  • 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 and Liability Insurance
    • FI 444, Life and Health Insurance
  • Data Mining Track
    • ST 521, Statistical Data Management
    • ST 522, Advanced Data Management
    • ST 531, Knowledge Discovery and Data Mining I
    • ST 532, Data Mining II
  • Quality and Six Sigma Track
    • ST 575, Statistical Quality Control
    • 3 hrs of Statistics Electives
    • IE 521, Reliability, Maintainability and Total Productive Maintenance
    • IE 622, Quality Engineering