Course Description
Events and probabilities (sample spaces), dependent and independent events, random variables and probability distribution, expectation, moment generating functions, multivariate normal distribution, sampling distributions.
Syllabus
Student Learning Outcomes, Goals, Objectives:
Students successfully completing this course will be able to:
understand the basic concepts of probability and its laws;
understand various discrete and continuous probability distributions;
be able to compute and interpret probabilities and moments associated with a probability density.
understand various sampling distributions;
appreciate the significance of Central Limit Theorem and its important role it plays in sampling;
apply the concepts and methods in solving real world problems.
Course Grading Information:
Activity/Performance Measure | Percentage/Points |
|---|---|
Homework | 30% |
Midterm 1 | 20% |
Midterm 2 | 20% |
Final Project | 30% |
Note: The UNCG Graduate School does not permit grades of D for graduate students. Therefore, any grade below 70 will be scored as an F for graduate students.
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- |
0-69 | F |
Attendance/Participation:
Attendance/participation is not a graded component included in the student's final grade for this course.
Course Materials Purchased by the Students:
John Freund’s Mathematical Statistics with Applications, 8th edition, by Miller & Miller, Pearson, ISBN: 9780134995373 (paperback) or ISBN: 978-0-321-80709-0 (hardcover).
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate, and inclusion of a reading does not imply endorsement.
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.