Research Methods and Statistics Courses
Research Methods (501). This course deals with research design and methodology in psychology. An important purpose of this course is to help students begin their predissertation research projects. Students explore issues of internal and external validity of research designs, examine the use of survey, case, observational, and experimental methods, and consider modes of data collection and levels of measurement as they examine a variety of research topics in clinical and developmental psychology in greater depth. Topics covered include basics of experimental design, measurement and scaling, microgenetic methods, diary studies, treatment efficacy research, and research ethics.
Multivariate Statistics (502). This course is designed to introduce students to advanced statistical techniques that are becoming increasingly important in developmental, clinical and school psychology research. We focus on understanding the advantages and limitations of common multivariate analytic techniques that permit simultaneous prediction of multiple outcomes. Emphasis is placed on helping students critically evaluate applications of these techniques in the literature and the utility of applying these techniques to their own work. Topics covered include path modeling, ways of analyzing data collected over multiple points in time (e.g., a growth curve capturing change in a developmental variable during childhood), confirmatory factor analysis, and measurement models. Students use existing data sets to gain experience with statistical software that can be used for multivariate analyses.
Statistics (505 or Social Work 540). Designed to help students develop the critical skills necessary to evaluate the research of others and to design and conduct research of their own. Students are presumed to have had exposure to statistics as undergraduates, but basic ideas and methods are reviewed quickly at the beginning of the semester. Topics covered in the course include simple and multiple correlation and regression, t-tests, nonparametric tests, analyses of variance, and methods of analyzing categorical data. The course stresses major theoretical concepts such as hypothesis-testing, uses of inferential methods, research design, validity, and power. Students gain experience analyzing data with SPSS and presenting the results of their analyses in APA-style.