The request to revise/create new Psychology and Health Psychology Ph.D. Program courses

Date: February 21, 2012
To: College of Liberal Arts & Sciences
From: Clarence Greene, Faculty Governance Assistant
Approved On: February 21, 2012
Implementation Date: 2012

Note: Deletions are strikethroughs. Insertions are underlined.

Catalog Copy

PSYC 6203. Research Design and Quantitative Methods I. (3) Cross-listed as PSYC 8102. Prerequisites: Admission to a Ph.D. program in Psychology or permission of the department. An overview of basic experimental and covariation research designs and the application of descriptive and inferential statistics to the designs. The focus will be on univariate designs, including simple and complex group comparisons, and basic correlational and linear regression strategies. (Fall)

PSYC 6204. Research Design and Quantitative Methods II. (3) Cross-listed as PSYC 8103. Prerequisites: Full graduate standing in a Psychology graduate program or permission of the instructor. An introduction to advanced experimental and covariation research strategies. The focus will be on a thorough exploration of applied multiple regression analysis. A brief introduction to selected multivariate models such as discriminant analysis, multivariant analysis of variance, log-linear models, factor analysis, and structural equation modeling will also be provided. (Spring)

PSYC 8102. Research Design and Quantitative Methods I Methodologies in Behavioral Sciences. (3) Cross-listed as PSYC 6203 and OSCI 8102. Prerequisites: Admission to a Ph.D. program inthe Health Psychology (HPSY) or the Organizational Science (OS ) doctoral programs, Psychology or by permission of the department instructor. An overview of basic experimental and covariation research designs and the application of descriptive and inferential statistics to the designs. Focuses on univariate designs, including simple and complex group comparisons, and basic correlational and linear regression strategies. (Fall) This interdisciplinary course provides a broad overview of the major research methodologies and methodological considerations in the behavioral sciences. Using examples drawn from the literature, the course focuses on general principles and perspectives of social science research. Topics include foundational concepts across the behavioral sciences (e.g., sampling, measurement, ethics, logic of hypothesis testing, etc.), and the evaluation of specific methodologies (e.g., experimentation, observation, survey, archival, epidemiological/ecological designs, etc.). Practical research considerations are also covered (e.g., basics of APA writing, IRB process and forms, data management and data cleaning, development of experimental protocols, etc). (Fall)

PSYC 8103. Basic Quantitative Analyses for Behavioral Sciences. Research Design and Quantitative Methods II. (3) Cross-listed as PSYC 6204 and OSCI 8103. Prerequisite: PSYC 8102 or equivalent. Introduction to quantitative data analysis and interpretation. This course focuses on the strategic application of the multiple regression and correlational framework (including specific instantiations such as ANOVA, path analyses, etc) including the incorporation of manipulated or categorical independent and categorical dependent variables. An introduction to advanced experimental and covariation research strategies. Focuses on a thorough exploration of applied multiple regression analysis. A brief introduction to selected multivariate models such as discriminant analysis, multivariate analysis of variance, log-linear models, factor analysis, and structural equation modeling is also provided. (Spring)

PSYC 8104. Advanced Quantitative Analyses for Behavioral Sciences. (3) Cross-list as OSCI 8104. Admission to the Health Psychology (HPSY) or the Organizational Science (OS) doctal programs or permission of the instructor. Prerequisite: PSYC 8103 or equivalent. A topical course that will focus on selected advance quantitative analyses used within behavioral sciences. Example topics: survival analysis, repeated measures analyses, latent model analyses, multi-level modeling, advanced categorical variable analyses, meta-analysis. May be repeated for credit as topics vary. (On demand).