Time Schedule:
Theodore P Beauchaine
PSYCH 523
Seattle Campus
Techniques of statistical computation using statistical software on personal computers and mainframe computers. Multiple regression, analysis of variance and covariance. Planned and post hoc comparisons and confidence intervals. Data analytic diagnostics for violations of regression assumptions. Prerequisite: PSYCH 522 and PSYCH 524, concurrent enrollment in PSYCH 525, or permission of instructor. Offered: W.
Class description
This course provides moderately detailed coverage of multiple linear regression and related data-analytic techniques. I assume that students are familiar with the logic of analysis of variance, that they have at least some exposure to correlation, and that they have used SPSS or a similar statistics package in the past. We begin with a brief overview of simple linear regression before moving on to multiple regression applications. A clear understanding of multiple linear regression provides the foundation for almost all statistical applications in psychology and related behavioral sciences. Students should emerge from this course with a foundation on which to build an effective data-analytic skill set.
Student learning goals
General method of instruction
Lecture and labs.
Recommended preparation
Psych 522 and 524 or equivalents. I strongly recommend that students do not fall behind in this class, as topics build on one another.
Class assignments and grading
Students complete assignments every week, both by hand and using the Statistical Package for the Social Sciences (SPSS). The SPSS assignments must be reported in APA format.
60% assignments, 40% tests (2).
