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Master's Degree

Program Prerequisites:

Grades of B or better in:

a complete calculus sequence up to multiple integration
a course in linear algebra
a course in probability
a course in statistical methods.

Typical Coursework:

(number of credit hours in parenthesis)

Fall Year 1: Stat 5620 (4), Stat 6620 (3)
Spring Year 1: Stat 6600 (4), Stat 6640 (3) [Take DGE at end of semester.]
Summer 1 Year 1: Elective (3)
Summer 2 Year 1: Elective (3)
Fall Year 2: Stat 6800 (3), Elective (3), Seminar (1)
Spring Year 2: Internship (3), Elective (3), Seminar (1)

Details of Coursework:

During their first year, our masters students take two main sequences:

Theory sequence: Stat 5620 and Stat 6600
This eight credit hour sequence covers the theoretical fundamentals for estimation and hypothesis testing.
Linear Models sequence: Stat 6620 and Stat 6640
This is a six credit hour sequence in linear regression and design of experiments. The current text is Neter, Kutner, Nachtsheim and Wasserman's 4th edition, Applied Linear Statistical Models supplemented by class notes. This sequence gives a thorough study of many of the most widely used topics in regression analysis and design of experiments. The emphasis is on applications and the computation of these procedures. The statistical software includes SAS, Minitab, and some Splus. Students may work with these software in the Statistical Computation Lab in a Sun workstation environment.

At the end of the first year, MS students must pass the Statistics Department Graduate Examinations (DGE), a written exam on the material covered in the two first year sequences. If a student fails this exam, he/she can retake it but they must eventually pass it to get a MS degree.

During the Fall Term of their second year, students take Stat 6800 which is a course in statistical computing. Students will learn to program using SAS macros as well as the SAS data step and procedures. The remaining course work is filled out by taking fifteen credit hours of elective coursework from the following list of electives:

Stat 5610: Applied Multivariate Statistics
Stat 5630: Sample Surveys
Stat 5650: Experimental Design for Quality Improvement
Stat 5660: Nonparametric Data Analysis
Stat 6670: Stochastic Processes
Stat 6680: Categorical Data Analysis
Stat 6690: Environmental Statistics
Stat 6810: Survival Data Analysis
Stat 6820: Time Series Analysis
Stat 6830: Robust Statistical Procedures
Stat 6840: Design of Experiments II (sequel to Stat 664)

These elective courses are a blend of theory and methods. All make use of statistical software and, for most of these courses, the predominant software used is SAS.

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