Data Analytics 310: Introduction to Statistical Methods exposes students to the process by which quantitative social science and data science research is conducted. The class revolves around three separate, but related tracks. Track one teaches some basic tools necessary to conduct quantitative social science research. Topics covered include descriptive statistics, sampling, probability, and statistical theory. Track two teaches students how to implement these basic tools using R. The third track teaches students the fundamentals of research design. Topics will include independent and dependent variables, generating testable hypotheses, and issues in causality.
Certificate students and individual course takers must complete DATA 101: Introduction to Data Analytics and Data Analytics 210: Intermediate Data Analytics before enrolling in this course. Although courses in the Certificate in Data Analytics must be taken sequentially to build your expertise in data analytics, you have the option to enroll in one or more courses in order without committing to the entire certificate. Students who complete all four courses in order earn the Certificate in Data Analytics.
Data Analytics courses admit a limited number of students each term. Early registration is recommended. To confirm whether registration is still open for a specific term before you enroll, please email firstname.lastname@example.org or call (215) 746-6903.
*Academic credit is defined by the University of Pennsylvania as a course unit (c.u.). A course unit (c.u.) is a general measure of academic work over a period of time, typically a term (semester or summer). A c.u. (or a fraction of a c.u.) represents different types of academic work across different types of academic programs and is the basic unit of progress toward a degree. One c.u. is usually converted to a four-semester-hour course.