Class description This class is a practical introduction to statistical modeling and experimental design, intended to provide essential skills for doing research. Students with research projects will be encouraged to share their experiences and project-specific questions. Students projects in statistics expected to attend class and participate in discussions.
Coursework will consist of two «practicals»—analyzing simple datasets to solidify core concepts—and two «case studies»—critical reading assignments of actual articles. Each assignment should take roughly one hour. Students are welcome to work in groups, but each student must submit an individual write-up in his or her own words. If you do work in a group, please also indicate with whom you worked. Finally, as this class is meant to be practical, we welcome any suggestions on topics and teaching style that will help you gain more from this course. What will you get out of this class? Schedule Due to the snowstorm and MIT closing on Tuesday, Jan 27, all classes from then on will be pushed back by one day.
Note that Practical 2 will still be due on Tuesday by email! Practicals Each of the practicals involves carrying out some statistical analysis on small, real-world datasets. Also explain and interpret the results of any exploratory data analysis and statisical inference. Your job is to provide succinct summaries of your analysis, not just copy-paste the computer output. Additional pointers for those using R: This short reference card contains a quick-lookup list of a lot of common functions. If you need more extensive data manipulation, this card is also a good reference.