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NS-231Probability and Statistics Lecture Schedule Tue: 02:00-03:15 Thu: 11:00-12:15 Semester Fall2014 Credit Hours Three Prerequisite Under Grad. Standing Instructor Adnan Ahmad Naeem Contact [email protected] Office S3/35 Office Hours Mon: 2.00:4.00 Tue: 10.00:2.00 Wed: 2.00:4.00 Thu: 2.00:4.00 Teaching Assistant None Contact N/A Measures of central tendency and dispersion, Moments, Introduction to classical Probability theory, Bayes theorem, Random variables (discrete Course Description and continuous), Probability distributions etc.), (Normal, Binomial, Poisson Expectation, Conditional distribution and conditional expectations, Correlation and regression. To develop an understanding of the basic concepts of probability and statistics and to develop among students the habit of basing their decisions on statistics and Information. Expected Outcomes 1. Probability & Statistics for Engineers & Scientists by Walpole, Myers 2. Engineering Statistics by D. C. Montgomery, John Wiley 3. Business Statistics by Mark L. Berenson and David Iivine. Textbooks Grading Policy Two Assignments: Best of 3 Quizzes: Midterm [In Class]: Final: 10% 15% 25% 50% Lecture Plan Lectures 1-4* 5-8* 9-10* Topics Introduction Measures of Central Tendency The Sample Mean The Median The Mode Measure of Dispersion Range The Variance & Standard Deviation Numerical Descriptive Measures for a Population The Population Mean Readings Numerical Descriptive Measures Numerical Descriptive Measures Numerical Descriptive Measures The Population Variance and Standard Deviation The Empirical Rule The Chebyshev Rule 11-14* 15-20* 21-25* 26-30* Linear Equations with One Independent Variable Least Square Criterion The Regression Line/Equation The Coefficient of Determination The Correlation Coefficient Scatterplot MIDTERM Probability Events, Sample Spaces and Probability Counting Rules Compound Events Complementary Events Conditional Probability Probability Rules for Unions and Intersections Bayes Rule Discrete Random Variables The Expected Value for a Discrete Random Variable Probability Distribution for Discrete Random Variable Binomial Probability Distribution The Poisson Probability Distribution Continuous Random Variables The Normal Probability Distribution Final Exam * - Tentative Correlation & Linear Regression Probability Theory Discrete Random Variables , Distributions Continuous Random Variables , Distributions
