Introduction to data science. Concepts of statistical thinking. Topics include random variables, sampling distributions, hypothesis testing, correlation and regression. Visualizing, analyzing and interpreting real world data using Python. Computing labs required.

No Prerequisites

5

Units

Optional

Grading

1, 2

Passtime

None

Level Limit

Letters and science

College
GEs Area C Quant Relationships
Unlocks ENV S 163A EEMB W 146 EEMB 146 SOC 205A PSY 10A MCDB 170
Disallowed majors prbio aqbio biocm biocs mcrbi phrma prbpy prpbs zool
T B A
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PHELP1513
M W
11:00 AM - 11:50 AM
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PHELP1513
M W
12:30 PM - 13:20 PM
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PHELP1513
M W
14:00 PM - 14:50 PM
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Summer 2024 . T B A
PSYCH1902
M T W R
09:30 AM - 10:50 AM
Summer 2024 . T B A
HSSB 1173
M T W R
08:00 AM - 09:20 AM
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PSTAT 5A Swenson J S Fall 2025 Total: 220
PSTAT 5A Adams A R Summer 2025 Total: 44
PSTAT 5LS
0 / 75 Enrolled
Statistics for Life Sciences
Katie Coburn 3.1
M T W R
12:30 PM - 13:50 PM
PSTAT 8
0 / 50 Enrolled
Transition to Data Science, Probability and Statistics
T B A
M T W R
09:30 AM - 10:50 AM
PSTAT 10
0 / 75 Enrolled
Principles of Data Science with R
T B A
M T W R
11:00 AM - 12:20 PM
PSTAT 10
0 / 75 Enrolled
Principles of Data Science with R
T B A
M T W R
11:00 AM - 12:20 PM
PSTAT 100
0 / 50 Enrolled
Data Science Concepts and Analysis
T B A
M T W R
15:30 PM - 16:35 PM
PSTAT 120A
0 / 100 Enrolled
Probability and Statistics
T B A
M T W R
14:00 PM - 15:05 PM