2 classes matched your search criteria.

Spring 2025  |  STAT 4052 Section 001: Statistical Machine Learning II (53103)

Instructor(s)
No instructor assigned
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Enrollment Requirements:
Stat 4051; and Stat 4102 or 5102
Times and Locations:
Regular Academic Session
 
01/21/2025 - 05/05/2025
Mon, Wed, Fri 10:10AM - 11:00AM
UMTC, East Bank
Enrollment Status:
Open (0 of 70 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/53103/1253

Spring 2025  |  STAT 4052 Section 002: Statistical Machine Learning II (53104)

Instructor(s)
No instructor assigned
Class Component:
Discussion
Times and Locations:
Regular Academic Session
 
01/21/2025 - 05/05/2025
Tue 10:10AM - 11:00AM
UMTC, East Bank
Auto Enrolls With:
Section 001
Enrollment Status:
Open (0 of 45 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/53104/1253

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