STAT 513 Bayesian Statistics

Bayesian statistics is an important topic for a statistician.  It differs from classical statistics in that it interprets probability as a measure of confidence or belief that can be updated with new data or evidence.

Textbook readings and lecture presentations

No details available.

Course Requirements Checklist

After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in the Course Overview.

Discussions (4)

Discussions are collaborative learning experiences. Therefore, the student is required to provide a thread in response to the provided prompt for each Discussion. Each thread must be at least 200 words. In addition to the thread, the student is required to reply to 1 other classmate’s thread with a minimum of 100 words. 

Homework Assignments (7)

Students will complete assigned problems from the textbook by uploading a handwritten or typed PDF file that clearly shows their process and final answer.

Bayesian Inference Project Assignments (2)

The student will apply concepts from the course to a dataset of his/her choosing. This project is submitted in two parts:

Bayesian Inference Project: Data Collection Proposal Assignment

The student will submit their data collection plan and proposed Bayesian method via Word document for approval.

Bayesian Inference Project: Video Presentation Assignment

This will be a video presentation and PowerPoint of the final results. The PowerPoint/video must be at least 15 minutes but not exceeding 20 minutes. The student must show his/her face in the video as well as the presentation.

Quizzes: Exams (2)

There will be one midterm exam and one final exam. Both exams will be open-book/open-notes, contain 1 file upload question, have a 4-hour time limit, and allow 1 attempt. The student will download the exam document linked in the quiz question, respond to the questions, and upload the document via the file upload link.