Course Syllabus
Contact Information
My interest has from an early age been in things mathematical - Physics and Math. In later life, I turned to Ancient Greek and statistics and earned a Ph.D. in Bayesian statistics at the University of Auckland New Zealand. These days I teach and develop classical and Bayesian statistics courses as well as innovate using the R workspace.
Course Details
For a list of course activities, scroll to the bottom of this page.
Course Prerequisites
- MATH 4733 - Mathematical Theory of Probability
- It would also be helpful to have a basic understanding of statistics, though it is not required.
Course Materials
- Statistics for Engineering and the Sciences 6th Edition by Mendenhall and Sincich (will be referred to as "MS" throughout the course)
- We will use Chapters 1-7 for this course, but you will also need this textbook for future courses.
- We will use Chapters 1-7 for this course, but you will also need this textbook for future courses.
- Installing R and Rstudio (free resource)
- You will need to install these programs for this course, and the installation program takes a little time. The sooner you start, the better!
- You will need to install these programs for this course, and the installation program takes a little time. The sooner you start, the better!
- Supplemental (not required purchase, but an excellent resource): An Introduction to Mathematical Statistics and Its Applications 6th edition, Larsen and Marx
- Data for the course: K25936_Downloads.zip
- An introduction to R package is available: Intro2R_0.1.0.tar.gz You may need some help with this - see the pages below:
Grades
Breakdown
| Activity | Description | Percentage |
|---|---|---|
| Mini Projects | These will require you to apply the knowledge gained in the module to a multi-step real-world problem. | 20 |
| Quizzes | This will require computations based on what you learned in the readings and lecture videos. There will be a mixture of true/false, multiple choice, and numeric answer problems. | 20 |
| Homework Assignments | There will be 4 total homework assignments which will happen about every 4 weeks. | 20 |
| Midterm | You will have one hour to complete 5 comprehensive questions, which will be a mix of short answer and long answer. | 20 |
| Final | You will have two hours to complete 10 comprehensive questions, which will be a mix of short answer and long answer. | 20 |
| Total | 100 |
Scale
| Percentage | Letter Grade |
|---|---|
| 90–100% | A |
| 80–89% | B |
| 70–79% | C |
| 60–69% | D |
| Below 60% | F |
Course Components
Module Overviews
For each module, you will have an introduction page that will provide an overview of the topic and prime you for what you are about to learn. It will also offer specific learning objectives and a to-do list to help you plan your week.
Quizzes
The quizzes will help to ensure that you have the foundational knowledge and/or component skills required for the course and will help inform you for the mini-projects, where you will be asked to apply or extend your learning. This auto-graded quiz holds you accountable for the resources and will help to check your understanding of key concepts. The Live session, if occurring on the week a quiz and mini-project is due, should be attended or watched before any work is uploaded or submitted.
Mini Projects
The questions are intended to give you practice in applying what you are learning in the week to a real problem. These will be formative, allowing you to get feedback along the way to help you succeed in the homework assignments and exams. You will have 3 tries to get the correct (numeric) answer, and you will have to upload evidence of your work (your "scratch paper").
Homework Assignments
About every 4 weeks (4 times throughout the semester), you will have homework encompassing what you have learned since the last homework assignment. This will allow the instructor to assess whether you have mastered the material and also give you any necessary feedback that might help you to improve your performance before the next exam.
Resources
Each week, you will be given resources (textbook readings, pre-recorded videos, etc.) to help you in solving the problem outlined at the beginning of the module. These resources will help you gain the foundational knowledge needed to do well on the weekly assessments and successfully participate in the Live Sessions.
Live Sessions
Every other week, you will attend or watch a recorded Live Session. The instructor will introduce the week’s project and offer good and bad examples of approaches to similar problems. Students will discuss the problem as a group and do group activities to scaffold each other’s knowledge of the topic at hand.
Midterm & Final
Twice during the semester, you will have comprehensive exams that will allow the instructor to assess your mastery over the course content. You will have one hour to complete each exam.
Course Policies
Communication
You may contact me through the help board on Canvas or by email if you have urgent and/or personal needs. My email address is wayne.s.stewart@ou.edu
The course help boards will be checked each day and you should get a response in less than 24 hours, Monday-Friday.
Feedback
Grading should be accomplished in less than a week and you should get feedback and an explanation for the grade you obtained.
Late Policy
Late work will not be accepted except for exceptional circumstances - family bereavement, sickness etc. All work will be given a zero if not submitted on time.
Cheating
I expect students to help one another, especially in the early stages of an assignment. However, the mass and bulk of the work submitted should be the student's own work.
University Academic Policies and Student Support
Access the University Academic Policies Document.
Course Summary:
| Date | Details | Due |
|---|---|---|