STAT_V 301 - T1A

Statistical Modelling for Data Science

Data analysis using statistical models and algorithms (e.g., linear and logistic regression, peeking, bandit, and variable selection algorithms) in case studies from different disciplines. Generative versus out-of-sample predictive models. Reproducible and transparent workflows for computer scripts and reports. [3-0-1] Prerequisite: STAT_V 201 and one of MATH_V 100, MATH_V 102, MATH_V 104, MATH_V 110, MATH_V 120, MATH_V 180, MATH_V 184, SCIE_V 001, MATH_O 100.

Section
STAT_V 301 -T1A
Campus
Vancouver
Delivery Mode
In person
Term
2026 Summer Session (UBC-V)
Instructional Format
Discussion
Credits
3.00
Start Date
End Date
Days
Thursday
Start Time
12:30 pm
End Time
01:30 pm

We acknowledge that UBC’s two main campuses are situated within the ancestral and unceded territory of the Musqueam people, and in the traditional, ancestral, unceded territory of the Syilx Okanagan Nation and their peoples.


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