(This article was originally published at Three-Toed Sloth , and syndicated at StatsBlogs.)

It's that time again:

- 36-402, Advanced Data Analysis, Spring 2013
*Description*: This course introduces modern methods of data analysis, building on the theory and application of linear models from 36-401. Topics include nonlinear regression, nonparametric smoothing, density estimation, generalized linear and generalized additive models, simulation and predictive model-checking, cross-validation, bootstrap uncertainty estimation, multivariate methods including factor analysis and mixture models, and graphical models and causal inference. Students will analyze real-world data from a range of fields, coding small programs and writing reports.*Prerequisites*: 36-401 (modern regression); or consent of instructor, in extraordinary cases*Time and place*: 10:30--11:50 am, Tuesdays and Thursdays, in Porter Hall 100*Note*: Graduate students in other departments wishing to take this course for credit need consent of the instructor, and should register for 36-608. Since this is primarily a class for undergraduate statistics majors, opportunities to do so are very limited.

Fuller details on the class homepage, including a detailed (but subject to change) list of topics, and links to the compiled course notes. I'll post updates here to the notes for specific lectures and assignments, like last time.

This is the same course I taught the last two springs, again at ninety-odd students from over a dozen majors.

Advanced Data Analysis from an Elementary Point of View

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