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Apr 20, 2024
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APST 663 - Design and Analysis of Experiments (3 units)
Statistical methods related to single factor, factorial, repeated measures and split-plot designs in social, life, and environmental sciences with emphasis on statistical programming.
Grading Basis: Graded
Units of Lecture: 3
Offered: Every Spring
Student Learning Outcomes
Upon completion of this course, students will be able to:
1. identify key elements in a prose research question or data description (cases/ experimental units, variables, types of variables/ levels of measurement) and make inferences about implicit causal assumptions and parameter of interest.
2. formulate hypotheses symbolically and in writing.
3. make analysis plans and combine statistical power analysis and real-world constraints to develop sample size targets.
4. construct detailed research action places for choosing statistics, implementing the proposed statistics, and testing the proposed hypotheses.
5. devise and defend a plan for managing missing data.
6. create outlines for reporting and interpreting results, as well as skeleton tables and graphs.
7. identify key elements in output, report accurately and succinctly upon them, and evaluate their implications for hypotheses.
8. demonstrate ability to use a reference manager program.
9. demonstrate ability to organize a multi-investigator project through file organization and management.
10. conduct an independent research project using methods learnt in the course.
11. present results from the independent research project to the class.
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