2 classes matched your search criteria.

Fall 2020  |  STAT 4052 Section 001: Introduction to Statistical Learning (16962)

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:
Open (43 of 50 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 Notes:
This course is completely online in a synchronous format. The course will meet online at the scheduled times. There will also be some asynchronous materials provided and details will be given in the syllabus.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/16962/1209

Fall 2020  |  STAT 4052 Section 002: Introduction to Statistical Learning (16963)

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 (43 of 50 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 Notes:
This course is completely online in a synchronous format. The course will meet online at the scheduled times. There will also be some asynchronous materials provided and details will be given in the syllabus.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/16963/1209

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