This 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.
Underpowered 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)
This course builds on your introductory knowledge of statistics and 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.
Dates: Nov 6 – Dec 4 | Final exams: Dec 5 and 6
Schedule: Mon/Wed 3:00-4:50 p.m.
Location: A158 Plant & Soil Science Bldg