This is a second course in statistical inference and is a further examination of statistics and data analysis beyond an introductory course. Topics include t-tools and permutation-based alternatives including bootstrapping, multiple-group comparisons, analysis of variance, linear regression, model checking, and refinement. Statistical computing and simulation-based emphasis is covered as well as basic programming in the R statistical package. Thinking statistically, evaluating assumptions, and developing tools for real-life applications are emphasized. Students may not count this course toward a degree if they have already completed STAT E-139, offered previously. Students cannot count both CSCI E-106 and STAT E-109 toward a degree or certificate.
Harvard Extension School
You may also like
- Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results,...