Nov 5 – Dec 5 2018 | MW 12:40-2:00p | 202 Biochemistry BuildingFinal student presentations: Dec 10 and 12 during regular class hours
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# OVERVIEWThis is a short (1-credit) intermediate-to-advanced course designed to:1) Discuss common misunderstandings & typical errors in the practice of statistical data analysis.2) Provide a mental toolkit for critical thinking and enquiry of analytical methods and results.Classes will involve lectures, discussions, hands-on exercises, and homework about concepts critical to the day-to-day use and consumption of quantitative/computational techniques.
# TOPICSUnderpowered statistics • Pseudoreplication • P-hacking & multiple hypothesis correction • Difference in significance & significant differences • Base rates & permutation tests • Regression to the mean • Descriptive statistics & spurious correlations • Estimation of error and uncertainty • (Others under consideration; Subject to small changes)
# PREREQUISITESThis is not an introductory course in statistics or programming. We will assume: 1) Familiarity with basic statistics & probability. 2) Ability to do basic data wrangling, analyses, & visualization using R or Python.• Strongly recommended MSU courses: CMSE 201 and CMSE 890 Sec 301-or-304 and Sec 302.• Contact Arjun for pointers to free online preparatory resources.
# INSTRUCTORArjun Krishnan, Dept. Computational Mathematics, Science and Engineering, Dept. Biochemistry and Molecular Biology | email@example.com | https://thekrishnanlab.org | https://twitter.com/compbiologist
Department of Computational Mathematics, Science and EngineeringDepartment of Biochemistry and Molecular BiologyMichigan State University