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Skidmore College · Courses

MS

8 courses with the subject MS, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.

MS 104Introduction to Statistics4

An introduction to fundamental concepts in statistical reasoning. Students will consider contexts, both historical and modern, in which statistical approaches arose and methodologies developed. Topics considered will include organization and analysis of data, the drawing of inferences from these data, and the careful presentation of these inferences. Examples will be drawn from a variety of disciplines.

Subject
MS
Credits (min)
4
Credits (max)
4
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu
MS 204Statistical Methods4

An introduction to statistical methods. Students will learn sampling strategies, exploratory data analysis, hypothesis testing, and randomization-based strategies, with examples from a variety of disciplines. This course is designed for majors in STEM fields and/or those with strong quantitative skills.

Subject
MS
Credits (min)
4
Credits (max)
4
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu
MS 210Data Visualization3

An introduction to data visualization. Students will learn to use data visualization tools, to objectively critique and redesign graphics, and to produce and describe visualizations using the R/RStudio statistical software. A willingness to code is needed. (Fulfills QR2 requirement).

Subject
MS
Credits (min)
3
Credits (max)
3
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu
MS 240Applied Regression Analysis4

A continuation of introductory statistics, this course is intended for students in the physical, social, or behavioral sciences. Topics include multiple linear regression, indicator variables, model diagnostics, transformations and selection strategies, logistic and multiple logistic regression, and analysis of variance. Emphasis will be on applying tools to real data as well as the interpretation of results. The class will make extensive use of the R/RStudio statistical software, which is free to download and use.

Subject
MS
Credits (min)
4
Credits (max)
4
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu
MS 251Topics in Statistics1-4

Topics that complement the established lower level course offerings in statistics will be selected. Emphasis will be on the nature of statistical thought.

Subject
MS
Credits (min)
1
Credits (max)
4
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu
MS 275HResearch Topics in Statistics1

Exploration of a research topic in statistics. The students, in collaboration with a faculty mentor, will participate in a research project in a particular area of statistics which may be related to the faculty member’s research program.

Subject
MS
Credits (min)
1
Credits (max)
1
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu
MS 351Topics in Statistics1-4

Topics that complement the established upper-level course offerings in statistics.

Subject
MS
Credits (min)
1
Credits (max)
4
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu
MS 371Independent Study1-4

Special study in statistics outside the regular department offerings.

Subject
MS
Credits (min)
1
Credits (max)
4
Credit unit
Credits
Type
course
Edition
2026-2027
Catalog
2026-2027 Catalog
Source
catalog.skidmore.edu

Source: Skidmore College's catalog, linked per course · table learning_unit · CourseShelf publish 61