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DATA SCIENCE MODELING I

STAT 240
Course Description

Introduces reproducible data management, modeling, analysis, and statistical inference through a practical, hands-on case studies approach. Topics include the use of an integrated statistical computing environment, data wrangling, the R programming language, data graphics and visualization, random variables and concepts of probability including the binomial and normal distributions, data modeling, statistical inference in one- and two- sample settings for proportions and means, simple linear regression, and report generation using R Markdown with applications to a wide variety of data to address open-ended questions.

Prerequisties

Satisfied Quantitative Reasoning (QR) A requirement

Satisfies
Credits

4

Offered

Not Applicable

Grade Point Average
3.51

1.98% from Historical

Completion Rate
98.54%

0.62% from Historical

A Rate
49.8%

19.38% from Historical

Class Size
753

77.36% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

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