STS 2560 Applied Nonparametric Statistics

This course focuses on data-oriented approaches to statistical estimation and inference using techniques that do not depend on the distribution of the variable(s) being assessed. Topics include classical rank-based methods, as well as modern tools such as permutation tests and bootstrap methods. The course will also introduce basic concepts and statistical methods associated with survival data including topics such as censoring, Kaplan-Meier estimation, logrank and related tests, and measures of risk. Advanced statistical software will be used, and written reports will link statistical theory and practice with communication of results.

Credits

4 sh

Prerequisite

STS 2120 or permission of the statistics program coordinator

Course Types

First-Year Foundation; Science

Offered

• Spring

Notes

Offered Spring of odd-numbered years.

Course Outcomes

1. Statistics promotes quantitative critical thinking skills that should serve you in the rest of your course studies at Elon. Specific outcomes that should prove valuable include the ability to:
   * Identify appropriate analyses given assumptions about the problem.
2. * Provide meaningful analysis of data using nonparametric methods.
3. * Identify appropriate nonparametric methods and their parametric counterparts for different analysis scenarios
4. * Effectively organize and communicate findings both visually and in writing.
5. * Assess confidence in results of statistical inference and make appropriate inferences about the population.
6. * Utilize analytical methods to produce numerical and graphical summaries of time-to-event data
7. * Conduct hypothesis testing to compare survival analysis functions
8. * Interpret results from studies in the literature that use survival analysis methods