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OverviewIntegrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields. The text first introduces the basics needed to understand and create tables and graphs produced by standard statistical software packages, such as Minitab, SAS, and JMP. It then takes students through the traditional topics of a first course in statistics. Novel features include: Applications of standard statistical concepts and methods to the analysis and interpretation of financial data, such as risks and returns Cox–Ross–Rubinstein (CRR) model, also called the binomial lattice model, of stock price fluctuations An application of the central limit theorem to the CRR model that yields the lognormal distribution for stock prices and the famous Black–Scholes option pricing formula An introduction to modern portfolio theory Mean-standard deviation diagram of a collection of portfolios Computing a stock’s betavia simple linear regression As soon as he develops the statistical concepts, the author presents applications to engineering, such as queuing theory, reliability theory, and acceptance sampling; computer science; public health; and finance. Using both statistical software packages and scientific calculators, he reinforces fundamental concepts with numerous examples. Full Product DetailsAuthor: Walter A. RosenkrantzPublisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.453kg ISBN: 9781032477787ISBN 10: 1032477784 Pages: 680 Publication Date: 21 January 2023 Audience: College/higher education , Tertiary & Higher Education Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsData Analysis. Probability Theory. Discrete Random Variables and Their Distribution Functions. Continuous Random Variables and Their Distribution Functions. Multivariate Probability Distributions. Sampling Distribution Theory. Point and Interval Estimation. Hypothesis Testing. Statistical Analysis of Categorical Data. Linear Regression and Correlation. Multiple Linear Regression. Single-Factor Experiments: Analysis of Variance. Design and Analysis of Multi-Factor Experiments. Statistical Quality Control. Appendix. Index.Reviews"""The book provides a very well-written, comprehensive treatment of all the standard requirements for an introductory course … Summing Up: Highly recommended."" —CHOICE, February 2009" The book provides a very well-written, comprehensive treatment of all the standard requirements for an introductory course ... Summing Up: Highly recommended. -CHOICE, February 2009 Author InformationWalter A. Rosenkrantz Tab Content 6Author Website:Countries AvailableAll regions |
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