Course Description
Introduction to probability models and statistical inference. Descriptive statistics, basic probability laws, discrete and continuous probability models, sampling distributions, central limit theorem, estimation, hypothesis testing, simple regression, and correlation. Prerequisite: Grade of C or better in MAT 196 or Grade of C or better in MAT 292 or concurrent registration in MAT 292 or permission of instructor.
Syllabus
Student Learning Outcomes, Goals, Objectives:
Students successfully completing this course will be able to:
- Perform data exploration using graphs and numbers.
- Understand probability models and their use in describing random phenomena.
- Understand the concept of random variables and their distributions.
- Understand sampling distributions.
- Understand the concepts of point estimation, hypothesis testing, and confidence intervals.
Course Grading Information:
| Activity/Performance Measure | Percentage/Points |
|---|---|
| Homework | 20% |
| In-Class Activity | 15% |
| Midterm 1 | 20% |
| Midterm 2 | 20% |
| Final Exam | 25% |
Grading Scale
| Percentage | Letter Grade |
|---|---|
| 93-100 | A |
| 90-92 | A- |
| 87-89 | B+ |
| 83-86 | B |
| 80-82 | B- |
| 77-79 | C+ |
| 73-76 | C |
| 70-72 | C- |
| 67-69 | D+ |
| 63-66 | D |
| 60-62 | D- |
| 0-59 | F |
Attendance/Participation:
Attendance at each class meeting is expected. In-class activities, which require class participation, account for 15% of the final grade.
Course Materials Purchased by the Students:
No course materials are required.
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.