3 classes matched your search criteria.
STAT 4052 is also offered in Spring 2025
STAT 4052 is also offered in Fall 2024
STAT 4052 is also offered in Spring 2024
STAT 4052 is also offered in Fall 2023
STAT 4052 is also offered in Spring 2023
STAT 4052 is also offered in Fall 2022
STAT 4052 is also offered in Spring 2022
STAT 4052 is also offered in Fall 2021
Spring 2022 | STAT 4052 Section 001: Introduction to Statistical Learning (55004)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
Regular Academic Session
Mon,
Wed,
Fri 10:10AM - 11:00AM
UMTC, East Bank
Mechanical Engineering 212
- Enrollment Status:
Open (41 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/55004/1223
Spring 2022 | STAT 4052 Section 002: Introduction to Statistical Learning (55005)
- Instructor(s)
- Class Component:
- Laboratory
- Times and Locations:
Regular Academic Session
UMTC, East Bank
Mechanical Engineering 212
- Auto Enrolls With:
- Section 001
- Enrollment Status:
Closed (35 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/55005/1223
Spring 2022 | STAT 4052 Section 003: Introduction to Statistical Learning (66723)
- Instructor(s)
- Class Component:
- Laboratory
- Times and Locations:
Regular Academic Session
UMTC, East Bank
Ford Hall 115
- Auto Enrolls With:
- Section 001
- Enrollment Status:
Open (6 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/66723/1223
ClassInfo Links - Spring 2022 Statistics Classes