2 classes matched your search criteria.

Spring 2024  |  STAT 3301 Section 001: Regression and Statistical Computing (54668)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Enrollment Requirements:
Stat 3021 and (CSCI 1113 or CSCI 1133), and co-requisite CSCI 2033
Times and Locations:
Regular Academic Session
 
01/16/2024 - 04/29/2024
Mon, Wed, Fri 12:20PM - 01:10PM
UMTC, East Bank
Anderson Hall 210
Enrollment Status:
Open (72 of 75 seats filled)
Also Offered:
Course Catalog Description:
This is a second course in statistics for students that have completed a calculus-based introductory course. Students will learn to analyze data with the multiple linear regression model. This will include inference, diagnostics, validation, transformations, and model selection. Students will also design and perform Monte Carlo simulation studies to improve their understanding of statistical concepts like coverage probability, Type I error probability, and power. This will allow students to understand the impacts of model misspecification and the quality of approximate inference. prereq: Stat 3021 and (CSci 1113 or CSci 1133), and co-requisite (CSci 2033 or Math 2142 or Math 2243 or Math 2373)
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/54668/1243

Spring 2024  |  STAT 3301 Section 002: Regression and Statistical Computing (65919)

Instructor(s)
Class Component:
Discussion
Credits:
4 Credits
Grading Basis:
A-F only
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Enrollment Requirements:
Stat 3021 and (CSCI 1113 or CSCI 1133), and co-requisite CSCI 2033
Times and Locations:
Regular Academic Session
 
01/16/2024 - 04/29/2024
Wed 08:00AM - 08:50AM
UMTC, East Bank
Nicholson Hall 35
Enrollment Status:
Open (72 of 75 seats filled)
Also Offered:
Course Catalog Description:
This is a second course in statistics for students that have completed a calculus-based introductory course. Students will learn to analyze data with the multiple linear regression model. This will include inference, diagnostics, validation, transformations, and model selection. Students will also design and perform Monte Carlo simulation studies to improve their understanding of statistical concepts like coverage probability, Type I error probability, and power. This will allow students to understand the impacts of model misspecification and the quality of approximate inference. prereq: Stat 3021 and (CSci 1113 or CSci 1133), and co-requisite (CSci 2033 or Math 2142 or Math 2243 or Math 2373)
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/65919/1243

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