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STAT 406 Methods for Statistical Learning
Flexible, data-adaptive methods for regression and classification models; regression smoothers; penalty methods; assessing accuracy of prediction; model selection; robustness; classification and regression trees; nearest-neighbour methods; neural networks; model averaging and ensembles; computational time and visualization for large data sets.
- Choose one section from all 2 activity types. (e.g. Lecture and Laboratory)
|Status||Section||Activity||Term||Interval||Days||Start Time||End Time||Comments|
|Full||STAT 406 101||Web-Oriented Course||1||Tue Thu||15:30||17:00|
As the course is on-line this term you DO NOT HAVE TO REGISTER FOR LABS!
Registration and wait list information can be found here: https://www.stat.ubc.ca/undergrad-registration-info-and-faqs
Please note that prerequisites are as stated in the UBC calendar. Registration will not be permited if lacking the stated prerequisite.
Seats reserved for Statistics specializations will be released on AUGUST 4th if not filled.
There will likely be a "mirrored" online class in the early evening as an alternative to the 3.30pm session
|STAT 406 WL1||Waiting List||1||Tue Thu||9:30||11:00|
Before registering on the wait list, please read the Registration and wait list FAQ page:
Please note that registration on the wait list does not guarantee a seat in the course