2 classes matched your search criteria.

Spring 2023  |  STAT 5401 Section 001: Applied Multivariate Methods (52994)

Instructor(s)
Class Component:
Lecture
Credits:
3 Credits
Grading Basis:
Student Option
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Enrollment Requirements:
STAT 3032 or 3301 or 3022 or 4102 or 5021 or 5102
Times and Locations:
Regular Academic Session
 
01/17/2023 - 05/01/2023
Mon, Wed, Fri 11:15AM - 12:05PM
UMTC, East Bank
Mechanical Engineering 108
Enrollment Status:
Open (55 of 56 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/52994/1233

Spring 2023  |  STAT 5401 Section 883: Applied Multivariate Methods (54775)

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
 
01/17/2023 - 05/01/2023
Mon, Wed, Fri 11:15AM - 12:05PM
Off Campus
UMN REMOTE
Enrollment Status:
Closed (1 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:
REGISTRATION FOR THIS SECTION IS PROCESSED THROUGH UNITE DISTRIBUTED LEARNING, NOT ONESTOP. See UNITE schedules at www.unite.umn.edu to view all courses offered through UNITE this semester and enroll for UNITE sections using the Registration Forms on that web site. UNITE is an educational office within the College of Science and Engineering. Students may enroll in UNITE sections of courses, with an additional UNITE fee of $100 per credit. All exams must be proctored by UNITE-approved proctor if taken off-campus. Course lectures are streamed live and available with same-day access to downloadable video and audio and streaming video archives. Questions - call 612-624-2332 or send a note to unite@umn.edu
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/54775/1233

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