The course will integrate exploratory data analysis and nonparametric statistical inference. The emphasis will be on analysis and interpretation of data. You should be familiar with summary statistics, graphs, hypothesis tests, confidence intervals and the basics of statistical inference.
Upon completion of this course students will:
- Ascertain if the assumptions for parametric statistical tests are reasonably met for a data set.
- Understand and implement permutation tests.
- Understand and implement nonparametric statistical test.
- Use statistical software to carry out various tests.
This graduate level course covers the following topics:
- Review Of Introductory Level Statistics
- One-Sample Tests
- Two-Sample Tests
- Two-Sample Tests
- Test for Variances
- One-Way Layout
- Patterned Alternatives
- Two-Way Layout
- Repeated Measures
- Trends and Correlation
- Other Topics (Time Permitting)
Dr. Tracey Hammel is the primary author of these course materials and has taught several different courses in the MAS program.
This course will use the statistical software program Minitab or R. See the Statistical Software page for more information.
Higgins, Jame V. (2003). Introduction to Modern Nonparametric Statistics. 1st Edition, Duxbury Press. ISBN-10: 0534387756.
Homework: The homework will consist of problems selected from the textbook or given within the notes and will be listed in the Homework schedule in Canvas.
Participation: The class will have discussion boards and you will be expected to follow the discussion boards and also participate in any discussions. You are also expected to keep up with all class communications and check Canvas on a regular basis.
Mid-Terms: The Midterms will be timed. They are to be submitted similarly to the Homework.
Final Exam: The final exam will be comprehensive (please see your course syllabus you receive upon enrollment for details).
- STAT 200, 401, 451, or 3 credits in statistics
- Logic skills.