Linear and multiple regression, analysis of residuals, transformations, variable and model selection including stepwise regression, and analysis of covariance. The course will stress the use of computer packages to solve real-world problems.

Prerequisites: PSTAT 10 and PSTAT 120B both with a minimum grade of C or better.

4

Units

Optional

Grading

1, 2

Passtime

None

Level Limit

Letters and science

College
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Spring 2024 . T B A
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08:00 AM - 09:15 AM
Summer 2026 . T B A
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PSTAT 126 Grigorian K Winter 2026 Total: 59
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PSTAT 126
94 / 100 Enrolled
Regression Analysis
Mengyang Michael Gu 3.9
M W
09:30 AM - 10:45 AM
PSTAT 120C
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Probability and Statistics
Jack Miller 4.7
M W
11:00 AM - 12:15 PM
PSTAT 120B
100 / 100 Full
Probability and Statistics
Amos Natido 4.1
M W
14:00 PM - 15:15 PM
PSTAT 120A
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Probability and Statistics
Carter A V
T R
09:30 AM - 10:45 AM
PSTAT 120A
244 / 300 Enrolled
Probability and Statistics
Natido A
T R
14:00 PM - 15:15 PM
PSTAT 122
150 / 150 Full
Design and Analysis of Experiments
Abuzaid A H
M W
14:00 PM - 15:15 PM
PSTAT 131
187 / 250 Enrolled
Introduction to Statistical Machine Learning
Katie Coburn 3.1
M W
17:00 PM - 18:15 PM