This course covers various statistical models used in empirical research, in particular human factors research, including linear regression, mixed linear models, non-parametric models, generalized linear models, time series modeling, and cluster analysis. For various observational and experimental data, students will be proficient in generating relevant hypotheses to answer research questions, selecting and building appropriate statistical models, and effectively communicating these results through interpretation and presentation of results. Basic knowledge in probability, statistics, and experimental design is required. The course will not focus on the design of experiments. In addition to homework assignments and exams, the students will review and critique journal articles and conference papers for the validity of the use of various statistical models. The students will work on a term long project of their choice and will be encouraged to relate this assignment to their current research projects. The examples used in class and the assignments will be drawn from human factors research. However, the students will not be required to use human factors data for their project.