Statistics

Topics cover include: Bivariate probability, continuous densities, generating functions. The exponential densities, including normal, t-, χ2 and F. Simple parametric and nonparametric tests. Further topics include the consistency, efficiency and sufficiency of estimates, maximum likelihood estimation; the central limit theorem, Chebyshev's inequality, the Neyman-Pearson lemma and the likelihood ratio test; regression, and analysis of variance.

This course examines the popular R language in the statistical analysis of data and the interpretation and communication of statistical findings. It covers exploratory data analysis, analysis of linear models including multiple regression and analysis of variance, generalized linear models including logistic regression and analysis of counts and time series analysis.

The course is designed to equip students with experience, knowledge, and skills for succeeding in globally interdependent and culturally diverse workplaces. During the course, students are challenged to question, reflect upon, and respond thoughtfully to the issues they observe and encounter in the internship setting and local host environment. Professional and personal development skills as defined by the National Association of Colleges and Employers (NACE), such as critical thinking, teamwork, and diversity are cultivated. Assignments focus on building a portfolio that highlights those competencies and their application to workplace skills. The hybrid nature of the course allows students to develop their skills in a self-paced environment with face-to-face meetings and check-ins to frame their intercultural internship experience. Students complete 45 hours of in-person and asynchronous online learning activities and 225-300 hours at the internship placement.