Introduction to Quantitative Research in Education: Regression Analysis
Description: Lecture, two hours; discussion, two hours. Requisite: course 150 or 151. Preparation: basic familiarity with programming language R. Introduction to regression as tool to answer questions about education. Regression is commonly used to answer questions about association claims--relationship between variables--and causal claims--causal effect of one variable on another. Using regression appropriately requires thoughtfulness about what kinds of questions regression can answer, about assumptions regression relies on, about limitations of our data, and about how particular variables (e.g., race and gender) are incorporated into analyses in order to avoid regression results that may be biased and may reify rather than interrogate problematic ideas. Emphasis on learning fundamental concepts of regression analysis and how these concepts can be thoughtfully applied to address different kinds of questions about education. Students are trained how to read and critically assess research and applications using R programming language. Letter grading.
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