APST 463 - 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.

Prerequisite(s): APST 207 or APST 270 or ECON 262 or PSY 210 or STAT 152 or STAT 352.

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.

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