### Engineering Probability and Statistics (STAT-223)

To introduce the basic concepts and engineering applications of probability and statistics. The course introduces the set theory, basic concepts of probability, conditional probability, independent events, Bayes’ theorem, discrete and continuous random variables, distributions and density functions, probability distributions (binomial, poisson, geometric, hyper geometric, N.B, poisson, uniform, normal and exponential), mean, variance , standard deviations, moments and moment generating functions. Linear regression, correlation and Curve fitting.

Catalog Data:             Course Code:                           STAT-22

Course Title:                            Engineering Probability and Statistics

Credit Hours:                           3+0 (3)

No of Sessions per week:        2 (Total 32 sessions)

Session Duration:                     90 min

Textbook:

1. Dr.M.Afzal Beg and Miraj Din Mirza, “Statistics Theory and Methods’’, 1st Edition, 2015

References:

1. A. Leon-Garcia, “Probability and Random processes for Electrical Engineering”. Pearson Education, 2nd edition 1994
2. Sheldon Ross, “ A first Course in Probability”. Pearson Education, 6th edition

​Course Learning Outcome (CLO):    Upon successful completion of this course, the student will be able to:

 CLO No Course Learning Outcome (CLO) Statements Assessment Tool CLO-1 Understand the purpose of statistics, set theory, and probability theory in the engineering field. Assignment 1,  Mid Term (8marks) CLO-2 Understand the concept of Conditional probability, events, and discrete and continuous random variables. Also, they will be able to use Bayes’ theorem in different engineering fields. Mid Term (12 marks), Assignment, 2 , Quiz Final Term Part 1 CLO-3 Compute the mean, variance, moments and moment generating functions of different discrete probability distributions (Binomial, Geometric, Hypergeometric, Poisson, and N.B) Mid Term (10 Marks), Assignment, 3, Quiz 1, Final Term Part 2 CLO-4 Compute the mean, variance, moments and moment generating functions of different continuous probability distributions (normal and exponential). Also will be able to understand the uses of linear regression and curve fitting. Assignment, 4, Final Term Part 3

Evaluation Criteria:

1. Assignments                                    15%

2. Quizzes                                            05%

3. Mid-Term Exam                                30%

4. Final Exam                                        50%