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
Unlocks PSTAT 127 PSTAT 197A PSTAT 220A PSTAT 115 PSTAT 131 PSTAT 231
These majors only finms stsds actsc stsap stats
ABUZAID A H
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Lecture

IV THEA2
T R
11:00 AM - 12:15 PM
0 / 100

Sections

PHELP1525
T
13:00 PM - 13:50 PM
0 / 25
PHELP1526
T
14:00 PM - 14:50 PM
0 / 25
PHELP1525
T
15:00 PM - 15:50 PM
0 / 25
PHELP1513
T
16:00 PM - 16:50 PM
0 / 25
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Fall 2024 . Abuzaid A H
NH 1006
T R
11:00 AM - 12:15 PM
Winter 2024 . Pandey P
PSYCH1924
T R
15:30 PM - 16:45 PM
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PSTAT 126 Mouti S Spring 2024 Total: 56
PSTAT 126 Pandey P Spring 2024 Total: 91
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PSTAT 126
0 / 100 Enrolled
Regression Analysis
Puja Pandey 4.3
T R
17:00 PM - 18:15 PM
40.0% A
PSTAT 126
0 / 125 Enrolled
Regression Analysis
Yuedong Wang 3.1
M W
12:30 PM - 13:45 PM
40.0% A
PSTAT 120A
0 / 300 Enrolled
Probability and Statistics
Brian Wainwright 3.0
M W
14:00 PM - 15:15 PM
30.9% A
PSTAT 122
0 / 100 Enrolled
Design and Analysis of Experiments
Chi P
M W
09:30 AM - 10:45 AM
45.4% A
PSTAT 122
0 / 125 Enrolled
Design and Analysis of Experiments
Chi P
M W
08:00 AM - 09:15 AM
45.4% A
PSTAT 130
0 / 125 Enrolled
SAS Base Programming
Julie Swenson 4.3
T
09:30 AM - 10:45 AM
36.1% A
PSTAT 131
0 / 80 Enrolled
Introduction to Statistical Machine Learning
Guo Yu 3.1
T R
12:30 PM - 13:45 PM
58.1% A
PSTAT 131
0 / 80 Enrolled
Introduction to Statistical Machine Learning
Guo Yu 3.1
T R
11:00 AM - 12:15 PM
58.1% A
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