Time Schedule:
Elizabeth Sanders
EDPSY 594
Seattle Campus
Multivariate analysis, including regression and multiple correlation; matrix algebra; factor analysis. Prerequisite: EDPSY 490 or equivalent. Offered: Sp.
Class description
Edpsy 594 provides students with statistical methods for answering research questions involving many variables, such as: **Does a combination of variables predict the outcome? **Do groups differ on a combination of outcomes? **Is there a basic underlying structure for the combination of variables? Course content includes matrix algebra, multiple regression and correlation, multivariate analysis of variance, and exploratory factor analysis. SPSS and Excel software used and taught as needed as part of the course (there is no separate lab to register for).
Student learning goals
General method of instruction
Lectures, readings, small-group exercises such as journal article discussions, and hands-on software practice in lab.
Recommended preparation
Proficiency in basic algebra and successful completion of Edpsy 490 (or equivalent univariate statistics course) are required. Edpsy 593 (experimental design and analysis with focus on analysis of variance methods) is helpful but not necessary.
Class assignments and grading
Homeworks generally involve datasets that are analyzed and interpreted in context (although computational work will be required for some problems). Individual project involves applying concepts learned to "real" data, and either presenting the project to the class or writing a brief paper about the project.
Grades are assigned via cumulative points earned from class participation, homeworks, and final project (with most weight given to homeworks).
