PROBABILITY & STATISTICS 21:640:327 (3 credits)
COURSE DESCRIPTION: Modern probability, statistics, and statistical inference; discrete and continuous distributions of random variables, statistical inference, hypothesis testing, and linear regression. PREREQUISITE: 21:640:119 (Basic Calculus), or 21:640:135 (Calculus I), or 21:640:155 (Honors Calculus I), or permission of instructor. TEXTBOOK: “Probability and Statistics for Engineers and Scientists,” fourth edition, by Anthony Hayter, published by Brooks/Cole (2012). DEPARTMENT WEB SITE: http://www.ncas.rutgers.edu/math THIS COURSE COVERS THE FOLLOWING: Chapter 1: Probability theory: probabilities, events, combination of events, conditional probability, probabilities of event intersections, posterior probabilities Chapter 2: Random variables: discrete random variables, continuous random variables, expectation of a random variable, variance of a random variable, combinations and functions of random variables Chapter 3: Discrete probability distributions: binomial distribution, hypergeometric distribution Chapter 5: Normal distribution: probability calculations using the normal distribution, linear combinations of normal random variables Chapter 7: Statistical estimations and sampling distributions: estimates, sampling distributions
point estimates, properties of point
Chapter 9: Comparing two population means: analysis of independent samples Chapter 10: Discrete data analysis: inferences on a population proportion, comparing two population proportions, goodness of fit tests for one-way contingency tables, testing for independence in two-way contingency tables
2 Chapter 12: Simple linear regression and correlation: simple linear regression model, fitting the regression line, inferences on the slope parameter 1 Department of Mathematics & Computer Science Smith Hall 216, 101 Warren Street, Newark, New Jersey 07102 Phone: (973) 353-5156 Fax: (973) 353-5270
