Schaum's Outline of Probability and Statistics (4版)

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Schaum's Outline of Probability and Statistics 4/e 作者：Murray R. Spiegel, John Schiller, R. Alu Srinivasan ISBN：9780071795579 版次：4 年份：2013 出版商：McGraw-Hill 頁數/規格：424頁/平裝單色 Description Tough Test Questions? Missed Lectures? Not Enough Time? Fortunately, there's Schaum's. This all-in-one-package includes more than 750 fully solved problems, examples, and practice exercises to sharpen your problem-solving skills. Plus, you will have access to 20 detailed videos featuring Math instructors who explain how to solve the most commonly tested problems--it's just like having your own virtual tutor! You'll find everything you need to build confidence, skills, and knowledge for the highest score possible. More than 40 million students have trusted Schaum's to help them succeed in the classroom and on exams. Schaum's is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test your skills. This Schaum's Outline gives you 897 fully solved problems Concise explanations of all course fundamentals Information on conditional probability and independence, random variables, binominal and normal distributions, sampling distributions, and analysis of variance Fully compatible with your classroom text, Schaum's highlights all the important facts you need to know. Use Schaum’s to shorten your study time--and get your best test scores! Schaum's Outlines--Problem Solved.

Probability and Statistics for Engineers and Scientists (4版)

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書名：Probability and Statistics for Engineers and Scientists 4/e 作者：HAYTER 出版社：Cengage 出版日期：2013/00/00 ISBN：9781111827045 內容簡介 ●Composition of the book allows flexibility in the order in which the material is taught. The material has been divided into four sections based on probability (Chapters 1-5), basic statistics (Chapters 6-10), advanced statistical methodologies (Chapters 11-14), and additional topics (Chapters 15-17). The Preface offers suggested paths that instructors may follow based on topic preference, making the book ideal for departments in which different methods of teaching coexist. ●This book can also serve as a handbook of statistical methodologies for undergraduate and graduate engineering students. ●Answers to all odd-numbered problems from the end-of-chapter sections are provided at the back of the book. ●Worked examples (77) and more than 150 data sets represent the many different areas of engineering; for instance, civil, mechanical, electrical, industrial, aerospace, biomedical, textile, chemical, and computing. ●Dozens of graphs, along with graphical tools, help students learn concepts visually. ●To help students grasp concepts, each topic is introduced with references to several real examples from engineering and the sciences. After the topic has been developed technically, a highlighted box reinforces students' learning by summarizing the important points. ●Many examples illustrate proper application of new methodologies, and are developed throughout the chapters as increasingly sophisticated methodologies are considered. This allows students to build on their learning in a manageable way, and understand connections among methodologies. ●Computer Note sections offer tips for using various software packages to perform analysis of data sets, which are referenced in the text and available for download from the book's website. ●The applied presentation emphasizes the understanding of underlying concepts and the application of statistical methodologies. 目錄 1. PROBABILITY THEORY. 2. RANDOM VARIABLES. 3. DISCRETE PROBABILITY DISTRIBUTIONS. 4. CONTINUOUS PROBABILITY DISTRIBUTIONS. 5. THE NORMAL DISTRIBUTION. 6. DESCRIPTIVE STATISTICS. 7. STATISTICAL ESTIMATION AND SAMPLING DISTRIBUTIONS. 8. INFERENCES ON A POPULATION MEAN. 9. COMPARING TWO POPULATION MEANS. 10. DISCRETE DATA ANALYSIS. 11. THE ANALYSIS OF VARIANCE. 12. SIMPLE LINEAR REGRESSION AND CORRELATION. 13. MULTIPLE LINEAR REGRESSION AND NONLINEAR REGRESSION. 14. MULTIFACTOR EXPERIMENTAL DESIGN AND ANALYSIS. 15. NONPARAMETRIC STATISTICAL ANALYSIS. 16. QUALITY CONTROL METHODS. 17. RELIABILITY ANALYSIS AND LIFE TESTING. Answers to Odd-Numbered Problems.