2 classes matched your search criteria.

Fall 2021  |  STAT 4052 Section 001: Introduction to Statistical Learning (22241)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Times and Locations:
Regular Academic Session
 
09/07/2021 - 12/15/2021
Mon, Wed, Fri 10:10AM - 11:00AM
UMTC, East Bank
Ford Hall 130
Enrollment Status:
Open (31 of 35 seats filled)
Also Offered:
Course Catalog Description:
This is the second semester of the core Applied Statistics sequence for majors seeking a BA or BS in statistics. Both Stat 4051 and Stat 4052 are required in the major. 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 classification, both classical methods of linear classification rules as well as modern computer-intensive methods of classification trees, and the estimation of classification errors by splitting data into training and validation data sets; non-linear parametric regression; nonparametric regression including kernel estimates; categorical data analysis; logistic and Poisson regression; and adjustments for missing data. Numerous datasets will be analyzed and interpreted, using the open-source statistical software R and Rstudio. prerequisites: STAT 4051 and (STAT 4102 or STAT 5102)
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/22241/1219

Fall 2021  |  STAT 4052 Section 002: Introduction to Statistical Learning (22242)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
Regular Academic Session
 
09/07/2021 - 12/15/2021
Tue 10:10AM - 11:00AM
UMTC, East Bank
Ford Hall 130
Auto Enrolls With:
Section 001
Enrollment Status:
Open (31 of 35 seats filled)
Course Catalog Description:
This is the second semester of the core Applied Statistics sequence for majors seeking a BA or BS in statistics. Both Stat 4051 and Stat 4052 are required in the major. 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 classification, both classical methods of linear classification rules as well as modern computer-intensive methods of classification trees, and the estimation of classification errors by splitting data into training and validation data sets; non-linear parametric regression; nonparametric regression including kernel estimates; categorical data analysis; logistic and Poisson regression; and adjustments for missing data. Numerous datasets will be analyzed and interpreted, using the open-source statistical software R and Rstudio. prerequisites: STAT 4051 and (STAT 4102 or STAT 5102)
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/22242/1219

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