The geometry of least squares; distribution theory for normal errors; regression, analysis of variance, and designed experiments; numerical algorithms (with particular reference to R); alternatives to least squares. Generalized linear models. Linear algebra and some acquaintance with statistics assumed. |
Instructor: | David Pollard |
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Office hours: | Tuesday 4:00 -- |
Time: | Tuesday, Thursday 9:00–10:15. |
Place: | 24 Hillhouse (Dana House), room 107 |
TA: | Michael Kane |