K310 | 9886 | Rickert, M

PSY K310 (K310) Statistical Techniques (3 cr.) M. Rickert Introduction to Statistical Inference Prerequisite: M119 or equivalent. The course begins with a brief review of commonly used methods for organizing and graphing data, i.e., data visualization. Basic descriptive statistics for summarizing the main characteristics of frequency distributions are then introduced, including measures of location, dispersion, and shape. Properties of the normal (Gaussian) distribution as well as important applications of the standard (unit) normal distribution will be presented. Next, we examine measures of the association between two variables, and develop a simple model for prediction based on linear regression. The critical conceptual shift to inferential statistics begins with a discussion of sampling procedures, elementary probability, and sampling distributions. Here, focus is on the binomial distribution and on the normal distribution as an approximation to the binomial. Methods for point estimation, interval estimation, and hypothesis testing (i.e., statistical decision-making under uncertainty) will be drawn primarily from the classical or "frequentist" perspective of statistical inference. A brief introduction to Bayesian inference will be presented; we will compare frequentist and Bayesian inference for hypothesis tests of a mean and for a test of the difference between two means. Other topics presented include estimation of effect size, power analysis, multiple-linear regression and correlation, analysis of variance and covariance, and non-parametric techniques such as chi-square tests for frequencies. Format: Two lectures per week (no lab); download assignments, supplementary materials, etc. from Oncourse. Homework: Five assignments (due dates TBA) Tests: Three in-class examinations, one final Text: Hinkle, D.E., Wiersma, W., and Jurs, S.G. (2003) Applied Statistics for the Behavioral Sciences (5th edition). Boston: Houghton Mifflin. Computer packages: (TBA but some computer exercises will require use of SPSS, Excel, and/or Matlab) Instructor(s): Regular office hours; other times by appointment; drop-ins and e-mail welcome.