Course description

Statistics is about understanding the world through data. We are surrounded by data, so there is a lot to understand. Covers data exploration and display, data gathering methods, probability, and statistical inference methods through contingency tables and linear regression. The emphasis is on thinking scientifically, understanding what is commonly done with data (and doing some of it for yourself), and laying a foundation for further study. Students learn to use statistical software and simulation tools to discover fundamental results. They use computers regularly; the test includes both multimedia materials and a software package. This course does not focus on data from any particular discipline, but will use real-world examples from a wide variety of disciplines and current events.

Students may receive credit for only one course in the following group: AEM 2100, BTRY 3010, BTRY 6010, ENGRD 2700, HADM 2010, HADM2011, ILRST 2100/STSCI 2100, ILRST 6100, MATH 1710, PUBPOL 2100, PUBPOL 2101 SOC 3010, STSCI 2150, STSCI 2200.

Prerequisites

Introductory algebra.

Winter 2025: Online course

Thomas DiCiccio
Thomas DiCiccio
Associate Professor

Winter 2025: Online course

Thomas DiCiccio
Thomas DiCiccio
Associate Professor