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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SAHA RAY R
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R
13:00 PM - 13:50 PM
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14:00 PM - 14:50 PM
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PHELP1513
R
15:00 PM - 15:50 PM
25 / 25 Full

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16:00 PM - 16:50 PM
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17:00 PM - 17:50 PM
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Spring 2024 . T B A
BUCHN1940
M W
08:00 AM - 09:15 AM
Spring 2024 . Pandey P
ILP 2101
T R
12:30 PM - 13:45 PM
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PSTAT 126 Saha Ray R Winter 2024 Total: 120
PSTAT 126 Saha Ray R Summer 2023 Total: 49
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Introduction to Statistical Machine Learning
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58.3% A