ENROLL Course Search

NOTE: There are some inconsistencies in the course listing data - ITS is looking into the cause.

Alternatives: For requirement lists, please refer to the current catalog. For up-to-the-minute enrollment information, use the "Search for Classes" option in The Hub. If you have any other questions, please email registrar@carleton.edu.

Saved Courses (0)

Your search for courses for 23/WI and with code: STATCORE found 3 courses.

Revise Your Search New Search

MATH 240.00 Probability 6 credits

Closed: Size: 30, Registered: 29, Waitlist: 0

CMC 301

MTWTHF
11:10am12:20pm11:10am12:20pm12:00pm1:00pm
Synonym: 64924

Laura Chihara

(Formerly Mathematics 265) Introduction to probability and its applications. Topics include discrete probability, random variables, independence, joint and conditional distributions, expectation, limit laws and properties of common probability distributions.

Prerequisite: Mathematics 120 or Mathematics 211

STAT 230.00 Applied Regression Analysis 6 credits

Open: Size: 28, Registered: 20, Waitlist: 0

CMC 102

MTWTHF
11:10am12:20pm11:10am12:20pm12:00pm1:00pm
Synonym: 65260

Claire Kelling

(Formerly Mathematics 245) A second course in statistics covering simple linear regression, multiple regression and ANOVA, and logistic regression. Exploratory graphical methods, model building and model checking techniques will be emphasized with extensive use of statistical software to analyze real-life data.

Prerequisite: Statistics 120 (formerly Mathematics 215), Statistics 250 (formerly Mathematics 275), Psychology 200, or AP Statistics Exam score of 4 or 5.

STAT 250.00 Introduction to Statistical Inference 6 credits

Open: Size: 30, Registered: 27, Waitlist: 0

CMC 306

MTWTHF
9:50am11:00am9:50am11:00am9:40am10:40am
Synonym: 65261

Katie St. Clair

(Formerly Mathematics 275) Introduction to modern mathematical statistics. The mathematics underlying fundamental statistical concepts will be covered as well as applications of these ideas to real-life data. Topics include: resampling methods (permutation tests, bootstrap intervals), classical methods (parametric hypothesis tests and confidence intervals), parameter estimation, goodness-of-fit tests, regression, and Bayesian methods. The statistical package R will be used to analyze data sets.

Prerequisite: Mathematics 240 Probability (formerly Mathematics 265)

Search for Courses

This data updates hourly. For up-to-the-minute enrollment information, use the Search for Classes option in The Hub

Instructional Mode
Class Period
Courses or labs meeting at non-standard times may not appear when searching by class period.
Requirements
You must take 6 credits of each of these.
Overlays
You must take 6 credits of each of these,
except Quantitative Reasoning, which requires 3 courses.
Special Interests