Prerequisite: MTH 230 or equivalent (Differential and Integral Calculus)

Instructor: Dr. Xinhui Zhang

Office Location: Room 234, Russ Engineering Center

Phone: 775-5151

Email: xinhui.zhang@wright.edu

Class Time: Tuesday and Thursday 10:25 am to 12:05 pm on, Room 103 Biological Sciences Building

Office Hours: T,Th 2:30 PM -3:30 PM

Course Objectives

Students will understand the mathematical concepts of probability and their application to problems involving probabilistic models and statistical thinking. Successful students will:

  1. Understand the definition of random variables and the relationship between distributions, distribution functions and outcomes.
  2. Understand and be able to apply concepts of conditional probability to problems.
  3. Understand the appropriate use of discrete and continuous probability distributions.
  4. Understand the concepts of expected value, variance and correlation and be able to derive results for these.
  5. Understand sampling experiments and the statistics associated with them.
  6. Understand estimators derived from sampling experiments, including maximum likelihood and method of moments estimators.
  7. Understand confidence intervals and hypothesis tests associated with statistical experiments and be able to interpret them appropriately.

The first four are related to probability and the remaining three to fundamentals of statistics.

Required Textbooks

 D.C. Montgomery, G.C. Runger, "Applied Statistics & Probability for Engineers", Third Edition, Wiley, ISBN 0-471-20454-4.

Grading:

There will be two midterm exams and a comprehensive final exam.  If a student requires a re-scheduled time for a midterm exam, he/she must notify the instructor in advance.   

Final grades will be based approximately on the following breakdown:

There will be homework assignments approximately every week. In-class quizzes will also be used to test your mastery of the current topic.

Hints for success in the course Understanding of probability and intuition about the effect of uncertainty on design and control of engineering systems will be a powerful addition to your toolbox of problem solving skills. This understanding can only come through repeated exposure and practice in the use of probability theory in the early parts of the course. Although often mathematical in nature at first, the intuition that you develop as you solve the homework problems will allow you to apply probabilistic reasoning.

A good strategy to prepare for the exams in the course is: choose any homework problem that you have solved correctly (or have read a correct solution for), but haven't looked at in, say, the last hour. You should be able to start from the problem statement, reason your way to the answer to the problem, and write the answer clearly as you would write the answer to an exam question, in a short period of time, without looking at the correct solution. When you can do this for all of the homework problems, you are close to being prepared.

In the later part of the course, the procedures we will study for carrying out the confidence interval and hypothesis test computations are relatively straightforward.  But do not make any errors on these computations. The more difficult part is careful interpretation of a problem statement, and careful interpretation of the result of the statistical (confidence interval or hypothesis test) procedure in the context of the problem statement.  After getting yourself organized to handle the mechanical computations for these procedures, you must focus on understanding the practical meaning of the results.

These are the two issues you will struggle with and master when you are successful in the course: 1) use of the correct probabilistic models and analysis, 2) interpretation of statistical results.

Late Assignments: Assignments are due at the beginning of class on the due date. Assignments turned in late on the due date (after the beginning of class) will incur a 10% penalty.


 

Honesty & Integrity: Students are expected be aware of and to adhere to the university standards of academic honesty. Violations include, but are not limited to, submitting work which is not your own for credit. Students may discuss homework assignments with others but, with the exception of explicit group assignments, are expected to complete and turn in their own work. Copying or sharing of work (including computer files) is prohibited, except as explicitly authorized by the instructors.

Attendance Policy: Students are expected to attend every lecture. However, circumstances may arise that prevent attendance (e.g., emergencies, weather). When circumstances arise, please inform me through email and take whatever steps are required to get caught up with the class.