2 classes matched your search criteria.

Spring 2021  |  EPSY 5261 Section 001: Introductory Statistical Methods (46946)

Instructor(s)
Class Component:
Lecture
Credits:
3 Credits
Grading Basis:
Student Option
Instructor Consent:
No Special Consent Required
Instruction Mode:
Completely Online
Class Attributes:
Online Course
Enrollment Requirements:
Exclude fr or soph 5000 level courses
Times and Locations:
Regular Academic Session
 
01/19/2021 - 05/03/2021
Tue, Thu 02:30PM - 03:45PM
Off Campus
UMN REMOTE
Enrollment Status:
Open (15 of 45 seats filled)
Also Offered:
Course Catalog Description:
EPSY 5261 is designed to engage students in statistics as a principled approach to data collection, prediction, and scientific inference. Students first learn about data collection (e.g., random sampling, random assignment) and examine data descriptively using graphs and numerical summaries. Students build conceptual understanding of statistical inference through the use of simulation-based methods (bootstrapping and randomization) before going on to learn parametric methods, such as t-tests (one-sample and two-sample means), z-tests (one-sample and two-sample proportions), chi-square tests, and regression. This course uses pedagogical methods grounded in research, such as small group activities and discussion. Attention undergraduates: As this is a graduate level course, it does not fulfill the Mathematical Thinking Liberal Education requirement. If you would like to take a statistics course in our department that fulfills that requirement, please consider EPSY 3264.
Class Notes:
This course will be taught remotely
Class Description:
This course is designed to provide an overview of introductory statistics. The topics to be covered in this course include graphing techniques, measures of center and spread, normal distributions, correlation, simple linear regression, sampling methods, experimental design, sampling distributions, and methods of statistical estimation and inference. Upon completion of this introductory course, students should be able to:(1) think critically about statistics used in popular magazines, newspapers, and journal articles, (2)apply the knowledge gained in the course to analyze simple statistics used in research, and (3)design a research study, use a statistical software package to analyze the data generated from this research study, and appropriately report the conclusions of this research study. Active participation is encouraged in this course, and many class periods will be spent working through activities, engaging in small- and large-group discussion, and learning how to use technology to solve different types of problems. Students will be expected to use SPSS in this course. A student-version of SPSS will be sold with the textbook, but this student version runs only on PCs, not on Macs. Any student who uses a Mac may need to complete SPSS work at a computer lab on campus.
Grading:
19% Final Exam
25% Reports/Papers
29% Quizzes
12% Class Participation
15% Problem Solving
Exam Format:
short-answer, multiple-choice true/false
Class Format:
10% Lecture
30% Discussion
30% Laboratory
30% Other Style class activities
Workload:
30 Pages Reading Per Week
20 Pages Writing Per Term
4 Exam(s)
3 Paper(s)
Other Workload: homework assignments
Textbooks:
https://bookstores.umn.edu/course-lookup/46946/1213
Instructor Supplied Information Last Updated:
21 May 2007

Spring 2021  |  EPSY 5261 Section 002: Introductory Statistical Methods (47103)

Instructor(s)
Class Component:
Lecture
Credits:
3 Credits
Grading Basis:
Student Option
Instructor Consent:
No Special Consent Required
Instruction Mode:
Completely Online
Class Attributes:
Online Course
Pre-Covid
Enrollment Requirements:
Exclude fr or soph 5000 level courses
Times and Locations:
Regular Academic Session
 
01/19/2021 - 05/03/2021
12:00AM - 12:00AM
Off Campus
Virtual Rooms ONLINEONLY
Enrollment Status:
Open (21 of 45 seats filled)
Also Offered:
Course Catalog Description:
EPSY 5261 is designed to engage students in statistics as a principled approach to data collection, prediction, and scientific inference. Students first learn about data collection (e.g., random sampling, random assignment) and examine data descriptively using graphs and numerical summaries. Students build conceptual understanding of statistical inference through the use of simulation-based methods (bootstrapping and randomization) before going on to learn parametric methods, such as t-tests (one-sample and two-sample means), z-tests (one-sample and two-sample proportions), chi-square tests, and regression. This course uses pedagogical methods grounded in research, such as small group activities and discussion. Attention undergraduates: As this is a graduate level course, it does not fulfill the Mathematical Thinking Liberal Education requirement. If you would like to take a statistics course in our department that fulfills that requirement, please consider EPSY 3264.
Class Notes:
This course will meet remote asynchronous. Students will be expected to participate in group discussions each week via google docs. Office hours will be held twice a week via Zoom and by appointment.. Contact the instructor with any questions (rao00013@umn.edu).
Class Description:
This course is designed to provide an overview of introductory statistics. The topics to be covered in this course include graphing techniques, measures of center and spread, normal distributions, correlation, simple linear regression, sampling methods, experimental design, sampling distributions, and methods of statistical estimation and inference. Upon completion of this introductory course, students should be able to:(1) think critically about statistics used in popular magazines, newspapers, and journal articles, (2)apply the knowledge gained in the course to analyze simple statistics used in research, and (3)design a research study, use a statistical software package to analyze the data generated from this research study, and appropriately report the conclusions of this research study. Active participation is encouraged in this course, and many class periods will be spent working through activities, engaging in small- and large-group discussion, and learning how to use technology to solve different types of problems. Students will be expected to use SPSS in this course. A student-version of SPSS will be sold with the textbook, but this student version runs only on PCs, not on Macs. Any student who uses a Mac may need to complete SPSS work at a computer lab on campus.
Grading:
19% Final Exam
25% Reports/Papers
29% Quizzes
12% Class Participation
15% Problem Solving
Exam Format:
short-answer, multiple-choice true/false
Class Format:
10% Lecture
30% Discussion
30% Laboratory
30% Other Style class activities
Workload:
30 Pages Reading Per Week
20 Pages Writing Per Term
4 Exam(s)
3 Paper(s)
Other Workload: homework assignments
Textbooks:
https://bookstores.umn.edu/course-lookup/47103/1213
Instructor Supplied Information Last Updated:
21 May 2007

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