University of California, Los Angeles 4 credits Social Science
Seminar, three hours. Preparation: knowledge of basic statistics. Advanced training in data analysis and statistics. Exploration of variation in data, development of models, and evaluation of these models through processing real-world data. Use of R and Jupyter notebooks to produce visualizations, conduct analyses, and write results. Models used extend skills to multivariate models (models with more than one explanatory variable), including multiple regression with both quantitative and categorical explanatory variables. Introduction also to models in which the explanatory variables interact with one another. Students carry out data analysis projects, produce a written data analysis report, and present their work. Letter grading.
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