3 classes matched your search criteria.

Fall 2020  |  STAT 4051 Section 001: Applied Statistics I (16580)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
Completely Online
Class Attributes:
Online Course
Times and Locations:
Regular Academic Session
 
09/08/2020 - 12/16/2020
Mon, Wed, Fri 10:10AM - 11:00AM
Off Campus
UMN REMOTE
Enrollment Status:
Closed (104 of 100 seats filled)
Also Offered:
Course Catalog Description:
This is the first semester of the Applied Statistics sequence for majors seeking a BA or BS in statistics. The course introduces a wide variety of applied statistical methods, methodology for identifying types of problems and selecting appropriate methods for data analysis, to correctly interpret results, and to provide hands-on experience with real-life data analysis. The course covers basic concepts of single factor analysis of variance (ANOVA) with fixed and random effects, factorial designs, analysis of covariance (ANCOVA), repeated measures analysis with mixed effect models, principal component analysis (PCA) and multidimensional scaling, robust estimation and regression methods, and rank tests. Numerous datasets will be analyzed and interpreted, using the open-source statistical software R and Rstudio. prerequisites: (STAT 3701 or STAT 3301) and (STAT 4101 or STAT 5101 or MATH 5651)
Class Notes:
This course is completely online in a synchronous format. The course will meet online at the scheduled times.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/16580/1209

Fall 2020  |  STAT 4051 Section 002: Applied Statistics I (16581)

Instructor(s)
Class Component:
Laboratory
Class Attributes:
Online Course
Times and Locations:
Regular Academic Session
 
09/08/2020 - 12/16/2020
Tue 09:05AM - 09:55AM
Off Campus
UMN REMOTE
Auto Enrolls With:
Section 001
Enrollment Status:
Closed (55 of 50 seats filled)
Course Catalog Description:
This is the first semester of the Applied Statistics sequence for majors seeking a BA or BS in statistics. The course introduces a wide variety of applied statistical methods, methodology for identifying types of problems and selecting appropriate methods for data analysis, to correctly interpret results, and to provide hands-on experience with real-life data analysis. The course covers basic concepts of single factor analysis of variance (ANOVA) with fixed and random effects, factorial designs, analysis of covariance (ANCOVA), repeated measures analysis with mixed effect models, principal component analysis (PCA) and multidimensional scaling, robust estimation and regression methods, and rank tests. Numerous datasets will be analyzed and interpreted, using the open-source statistical software R and Rstudio. prerequisites: (STAT 3701 or STAT 3301) and (STAT 4101 or STAT 5101 or MATH 5651)
Class Notes:
This course is completely online in a synchronous format. The course will meet online at the scheduled times.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/16581/1209

Fall 2020  |  STAT 4051 Section 003: Applied Statistics I (16582)

Instructor(s)
Class Component:
Laboratory
Class Attributes:
Online Course
Times and Locations:
Regular Academic Session
 
09/08/2020 - 12/16/2020
Tue 10:10AM - 11:00AM
Off Campus
UMN REMOTE
Auto Enrolls With:
Section 001
Enrollment Status:
Open (49 of 50 seats filled)
Course Catalog Description:
This is the first semester of the Applied Statistics sequence for majors seeking a BA or BS in statistics. The course introduces a wide variety of applied statistical methods, methodology for identifying types of problems and selecting appropriate methods for data analysis, to correctly interpret results, and to provide hands-on experience with real-life data analysis. The course covers basic concepts of single factor analysis of variance (ANOVA) with fixed and random effects, factorial designs, analysis of covariance (ANCOVA), repeated measures analysis with mixed effect models, principal component analysis (PCA) and multidimensional scaling, robust estimation and regression methods, and rank tests. Numerous datasets will be analyzed and interpreted, using the open-source statistical software R and Rstudio. prerequisites: (STAT 3701 or STAT 3301) and (STAT 4101 or STAT 5101 or MATH 5651)
Class Notes:
This course is completely online in a synchronous format. The course will meet online at the scheduled times.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/16582/1209

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