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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PANDEY P
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SSMS 1303
R
14:00 PM - 14:50 PM
30 / 30 Full

ILP 4105
R
15:00 PM - 15:50 PM
30 / 30 Full

ILP 4105
R
16:00 PM - 16:50 PM
30 / 30 Full

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Winter 2024 . Pandey P
PSYCH1924
T R
15:30 PM - 16:45 PM
Fall 2024 . Pandey P
ILP 1101
T R
17:00 PM - 18:15 PM
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PSTAT 126 Pandey P Winter 2025 Total: 96
PSTAT 126 Pandey P Fall 2024 Total: 173
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PSTAT 126
0 / 100 Enrolled
Regression Analysis
T B A
M W
08:00 AM - 09:15 AM
42.3% A
PSTAT 126
76 / 100 Enrolled
Regression Analysis
Saad Mouti 2.4
T R
08:00 AM - 09:15 AM
42.3% A
PSTAT 120A
94 / 94 Full
Probability and Statistics
Pandey P
T R
14:00 PM - 15:15 PM
31.5% A
PSTAT 122
99 / 100 Enrolled
Design and Analysis of Experiments
Saha Ray R
T R
11:00 AM - 12:15 PM
50.5% A
PSTAT 122
0 / 125 Enrolled
Design and Analysis of Experiments
Saha Ray R
T R
11:00 AM - 12:15 PM
50.5% A
PSTAT 122
100 / 100 Full
Design and Analysis of Experiments
Saha Ray R
M W
11:00 AM - 12:15 PM
50.5% A
PSTAT 130
125 / 125 Full
SAS Base Programming
Julie Swenson 4.3
T
08:00 AM - 09:15 AM
35.8% A
PSTAT 131
100 / 100 Full
Introduction to Statistical Machine Learning
Katie Coburn 3.3
T R
15:30 PM - 16:45 PM
58.3% A