2 classes matched your search criteria.

Spring 2021  |  STAT 5401 Section 001: Applied Multivariate Methods (49888)

Instructor(s)
Class Component:
Lecture
Credits:
3 Credits
Grading Basis:
Student Option
Instructor Consent:
No Special Consent Required
Instruction Mode:
Completely Online
Class Attributes:
Online Course
Enrollment Requirements:
STAT 3032 or 3301 or 3022 or 4102 or 5021 or 5102
Times and Locations:
Regular Academic Session
 
01/19/2021 - 05/03/2021
Mon, Wed, Fri 11:15AM - 12:05PM
Off Campus
UMN REMOTE
Enrollment Status:
Open (49 of 50 seats filled)
Also Offered:
Course Catalog Description:
Bivariate and multivariate distributions. Multivariate normal distributions. Analysis of multivariate linear models. Repeated measures, growth curve, and profile analysis. Canonical correlation analysis. Principal components and factor analysis. Discrimination, classification, and clustering. pre-req: STAT 3032 or 3301 or 3022 or 4102 or 5021 or 5102 or instr consent Although not a formal prerequisite of this course, students are encouraged to have familiarity with linear algebra prior to enrolling. Please consult with a department advisor with questions.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/49888/1213

Spring 2021  |  STAT 5401 Section 881: Applied Multivariate Methods (66711)

Instructor(s)
Class Component:
Lecture
Credits:
3 Credits
Grading Basis:
Student Option
Instructor Consent:
No Special Consent Required
Instruction Mode:
Completely Online
Class Attributes:
UNITE Distributed Learning
Enrollment Requirements:
STAT 3032 or 3301 or 3022 or 4102 or 5021 or 5102
Times and Locations:
Regular Academic Session
 
01/19/2021 - 05/03/2021
Mon, Wed, Fri 11:15AM - 12:05PM
Off Campus
UMN REMOTE
Enrollment Status:
Closed (2 of 0 seats filled)
Also Offered:
Course Catalog Description:
Bivariate and multivariate distributions. Multivariate normal distributions. Analysis of multivariate linear models. Repeated measures, growth curve, and profile analysis. Canonical correlation analysis. Principal components and factor analysis. Discrimination, classification, and clustering. pre-req: STAT 3032 or 3301 or 3022 or 4102 or 5021 or 5102 or instr consent Although not a formal prerequisite of this course, students are encouraged to have familiarity with linear algebra prior to enrolling. Please consult with a department advisor with questions.
Class Notes:
UNITE
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/66711/1213

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