Jun 12-Jul 28, 2017
Credit: 3 graduate
Instructor(s): Phil Kaatz
Course DescriptionPlease register for CRN 10334
Stochastic concepts including probabilistic underpinnings of statistics, measures of central tendency, variability, correlation, distributions, sampling, and simulation. Exploratory data analysis including experiments, surveys, measures of association and inferential statistics. Discussion of methods for teaching statistics in secondary mathematics and science.
This course is designed to engage students using a modeling and simulation approach to inference. This course uses pedagogical principles that are founded in research, such as weekly small group discussion activities, in addition to the collection of weekly homework assignments. In this course, students will be exposed to numerous examples of real-world applications of statistics that are designed to help them think like statisticians and develop a conceptual understanding of statistics. Upon completion of this course, students should have an understanding of the foundational concepts of data, variation and inference, as well as an appreciation for the fundamental role that statistics plays in a host of disciplines, such as business, economics, law, and medicine.
Meeting Place and Times
This course is taught online. Course participants login and participate at a time of day that is convenient for them. It is recommended that participants login at least 4 to 6 times per week and plan on spending as much as 20 hours per week for 7 weeks to successfully complete this 3 credit graduate course. It is imperative that teachers are available to participate fully in the course for the full 7 weeks. This time estimate includes both the time teachers spend on-line connected to Desire2Learn participating in group discussions and other course activities and the time spent off-line working on assignments, projects, and lab activities.
Instructor(s)Phil Kaatz, PhD.
Target AudienceHigh school or community college mathematics and science teachers.
Time Commitment:15-20 hours per week. If you are unfamiliar with this field of study and/or method of delivery, you may require more time.
Tuition and Fees
If you are accepted into a qualified online program, see the appropriate MSU Online Only Tuition and Fee table below:
If you are also taking a face-to-face course, please refer to the MSU Fee Schedules.
This course uses a learning management system. You will learn more closer to the course start date.
For More Information
Contact Philip Kaatz at firstname.lastname@example.org
How to Register
You must be accepted as a student to Montana State University to take this course.
Learn how to apply.
After your application has been accepted, you will register via MSU's online registration system, MyInfo.
Registration requires a PIN number. Learn how to find your PIN.
Once you have your PIN, learn how to register through MyInfo.