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Nov 10, 2024
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STAT 673 - Nonparametric Statistical Methods Units: 2 Nonparametric methods and distribution-free inferential methods. Topics include: Permutation methods, bootstrapping, and re-sampling methods. Hypothesis testing and estimation procedures. Exact, Monte-Carlo, and asymptotic p-values. Measures of association.
Prerequisites: STAT 631 and STAT 632. Possible Instructional Methods: On-ground. Grading: A-F grading only. Student Learning Outcomes - Upon successful completion of this course students will be able to: - apply appropriate methods to describe and present data in summaries, tables, and graphs.
- formulate solutions to problems and develop nonparametric methods for the analysis of data.
- formulate statistical hypotheses using distribution-free methods.
- use statistical software to analyze data using nonparametric methods.
- communicate results to others regarding nonparametric analysis of data.
- understand the theory, concepts, and terminology of nonparametric statistical methods at a level that supports lifelong learning of appropriate methodologies.
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