This course introduces students to the tools and logic used by social scientists to measure social phenomena and address key research questions. Students will learn to define variables, develop hypotheses, explore relationships between variables, and use statistical techniques to make inferences about populations based on sample data. The course emphasizes both conceptual understanding and practical application of quantitative methods.

Main topics include measurement, levels of measurement, descriptive and inferential statistics, normal distributions, and sampling methods. Students will also engage with cross-tabulations, Chi-Square tests, measures of association (Lambda and Gamma), and regression analysis. Through these methods, they will develop skills in interpreting statistical outputs, including p-values, confidence intervals, regression coefficients, and the coefficient of determination (R²).

By the end of the course, students will be equipped to analyze relationships between variables using both bivariate and multiple regression techniques. They will also understand how statistical controls work and how to interpret results in real-world sociological research. Prerequisites include SOC100 or SOC150, with recommended preparation in SOC150.