This course will introduce you to the major statistical techniques in the field of psychology. Covers the use of large and small samples for statistical inference, linear and multiple regression, time series models and forecasting, nonparametric methods, the chi square test for cell probabilities, and contingency tables. Statistical packages for the social sciences will be studied in depth.
This course is designed for the applied social science researchers at the advanced undergraduate or beginning graduate level. It is assumed that you have had a one semester course in introductory statistics that covered measures of central tendency, measures of variability, standard scores (z, T, stanines, etc.), correlation, and inferential statistics, including at least the t tests for independent and dependent samples. In unit 1, we review briefly some descriptive statistics, summation notation, and testing for a “significant” difference. This unit is not intended to thoroughly teach this material again, but to refresh your memory.
The emphasis in the course is on conceptual understanding of the statistical techniques, learning how to effectively use statistical software to run the analyses, and learning how to interpret the computer printout that results from such runs. One major statistical package, SPSS (Statistical Package for the Social Sciences), is an integral part of this course. Details on SPSS are given in IBM SPSS Statistics 22.