2 classes matched your search criteria.

Summer 2020  |  STAT 3032 Section 001: Regression and Correlated Data (82970)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
Completely Online
Class Attributes:
Online Course
Meets With:
STAT 5302 Section 001
Times and Locations:
Regular Academic Session
 
06/08/2020 - 07/31/2020
Mon, Tue, Wed, Thu 01:25PM - 03:20PM
Off Campus
Virtual Rooms ONLINEONLY
Enrollment Status:
Open (42 of 50 seats filled)
Also Offered:
Course Catalog Description:
This is a second course in statistics with a focus on linear regression and correlated data. The intent of this course is to prepare statistics, economics and actuarial science students for statistical modeling needed in their discipline. The course covers the basic concepts of linear algebra and computing in R, simple linear regression, multiple linear regression, statistical inference, model diagnostics, transformations, model selection, model validation, and basics of time series and mixed models. Numerous datasets will be analyzed and interpreted using the open-source statistical software R. prereq: STAT 3011 or STAT 3021
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/82970/1205

Summer 2020  |  STAT 3032 Section 002: Regression and Correlated Data (82971)

Instructor(s)
Class Component:
Laboratory
Class Attributes:
Online Course
Times and Locations:
Regular Academic Session
 
06/08/2020 - 07/31/2020
Fri 01:25PM - 03:20PM
Off Campus
Virtual Rooms ONLINEONLY
Auto Enrolls With:
Section 001
Enrollment Status:
Open (42 of 50 seats filled)
Course Catalog Description:
This is a second course in statistics with a focus on linear regression and correlated data. The intent of this course is to prepare statistics, economics and actuarial science students for statistical modeling needed in their discipline. The course covers the basic concepts of linear algebra and computing in R, simple linear regression, multiple linear regression, statistical inference, model diagnostics, transformations, model selection, model validation, and basics of time series and mixed models. Numerous datasets will be analyzed and interpreted using the open-source statistical software R. prereq: STAT 3011 or STAT 3021
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/82971/1205

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