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Sep 04, 2024
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STAT 641 - Bootstrapping Methods Units: 2 Implementation of computationally-advanced statistical methods. Use of modern computing software (e.g. R, Python, SAS). Topics may include: bootstrap, Monte Carlo, and applied statistics.
Prerequisites: STAT 640. Possible Instructional Methods: On-ground, or Hybrid, or Online-Asynchronous. Grading: A-F grading only. Student Learning Outcomes - Upon successful completion of this course students will be able to:
- Derive and understand the theory of point and interval estimation and hypothesis testing.
- Formulate and model practical problems for solutions using these statistical methodologies.
- Produce relevant computer output using standard statistical software and interpret results appropriately.
- Communicate statistical concepts and analytical results clearly and appropriately to others.
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