Sociologists and other social scientists must describe and interpret social facts in order to make sense of the world around them. To do this, they often rely on the analysis of quantitative data using statistical methods. This course acts as a primer to sociological statistical analysis and students will learn to find and access social data, summarize patterns in that data, represent these patterns graphically, and explore relationships between different variables. Topics include descriptive measures, hypothesis testing, analysis of variance, chi-square, correlation, and regression. This course is designed as a gateway to quantitative sociological research, and emphasis is on practice and implementation, with students also learning to use SPSS software.
Satisfies the Mathematical and Quantitative Thought distribution requirement.
Satisfies a requirement in the Data Science interdisciplinary minor.