University of California, Los Angeles 4 credits Statistics
Lecture, three hours; discussion, one hour. Requisite: course 402. Recommended: course 413. Preparation: working knowledge of R. Limited to Master of Applied Statistics and Data Science students. Examination of the theory and practice of statistical consulting in data science. Addresses consulting problems in collaborative and interdisciplinary settings. Application of statistical methods, including hierarchical linear modeling, survey design and evaluation, reliability and validity assessment, factor-analytic methods, and sample size and power analysis to real-world consulting questions. Evaluation of ethical issues in statistics, data science, and artificial intelligence, including fairness, transparency, accountability, and sources of bias. Development of communication, collaboration, and problem-solving skills through a team-based consulting project. Letter grading.
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