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
No info found

Lecture

IV THEA2
T R
11:00 AM - 12:15 PM
33 / 100

Sections

PHELP1525
T
13:00 PM - 13:50 PM
16 / 25
PHELP1526
T
14:00 PM - 14:50 PM
9 / 25
PHELP1525
T
15:00 PM - 15:50 PM
5 / 25
PHELP1513
T
16:00 PM - 16:50 PM
3 / 25 Closed
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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
See All
PSTAT 126 Mouti S Spring 2024 Total: 56
PSTAT 126 Pandey P Spring 2024 Total: 91
See All
PSTAT 126
100 / 100 Full
Regression Analysis
Puja Pandey 4.3
T R
17:00 PM - 18:15 PM
40.0% A
PSTAT 126
104 / 125 Enrolled
Regression Analysis
Yuedong Wang 3.1
M W
12:30 PM - 13:45 PM
40.0% A
PSTAT 120B
150 / 150 Full
Probability and Statistics
Katie Coburn 3.4
T R
17:00 PM - 18:15 PM
40.0% A
PSTAT 122
100 / 100 Full
Design and Analysis of Experiments
Chi P
M W
09:30 AM - 10:45 AM
45.4% A
PSTAT 122
99 / 125 Enrolled
Design and Analysis of Experiments
Chi P
M W
08:00 AM - 09:15 AM
45.4% A
PSTAT 130
125 / 125 Full
SAS Base Programming
Julie Swenson 4.3
T
09:30 AM - 10:45 AM
36.1% A
PSTAT 131
80 / 80 Full
Introduction to Statistical Machine Learning
Guo Yu 3.1
T R
12:30 PM - 13:45 PM
58.1% A
PSTAT 131
80 / 80 Full
Introduction to Statistical Machine Learning
Guo Yu 3.1
T R
11:00 AM - 12:15 PM
58.1% A