This course introduces Master’s students to basic statistical concepts using real-world examples and hands-on exercises. Students will learn the science and art of appreciating the uses of statistics in social science, public policy, management, and everyday life. The course explores topics that include descriptive statistics (e.g., mean, standard deviation, variance, correlation, chi-square) to inferential statistics (e.g., multiple regression, logistic regression, factor analysis, ANOVA/MANOVA, conjoint analysis), with a particular focus on understanding the conditions under which various statistical techniques may be properly used. Given the importance of computing tools and software for statistical analysis, a portion of the class time will be devoted to helping students become familiar with statistical packages. SPSS will be the main software used in the course while R will also be introduced at some point in the course. At the end of this course, students will 1) be able to interpret statistical findings of various kinds, 2) become a qualified “consumer” of statistics presented in scholarly journals, and 3) prepare themselves for future research/capstone projects with a quantitative component.

Continuous Assessment: 100%