The geometry of least squares; distribution theory for normal errors; regression, analysis of variance, and designed experiments; numerical algorithms (with particular reference to S-plus); alternatives to least squares. Generalized linear models. After Statistics 242b and Mathematics 222 or equivalents. |
Instructor: | David Pollard |
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Email: | david.pollard@yale.edu |
Office hours: | Thurs 12:00–1:15 or immediately after lectures |
Time: | Tuesday, Thursday 9:00–10:15. |
Place: | 24 Hillhouse (Dana House), room 107 |
TA: | Peter Radchenko |