Schaum's Outline of Probability and Statistics, 4th Edition

Schaum's Outline of Probability and Statistics, 4th Edition

Schaum's Outline of Probability and Statistics, 4th Edition

Schaum's Outline of Probability and Statistics, 4th Edition

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Overview

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'sto help them succeed in the classroom and on exams.Schaum's is the key to faster learning and highergrades in every subject. Each Outline presents all theessential 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 andindependence, 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.


Product Details

ISBN-13: 9780071795579
Publisher: McGraw Hill LLC
Publication date: 12/11/2012
Series: Schaum's Outline Series
Edition description: List
Pages: 432
Sales rank: 314,749
Product dimensions: 8.10(w) x 10.70(h) x 0.90(d)

About the Author

The Late MURRAY R. SPIEGEl received the M.S degree in Physics and the Ph.D. in Mathematics from Cornell University. He had positions at Harvard University, Columbia University, Oak Ridge and Rensselaer Polytechnic Insitute, and served as a mathematical consultant at several large Companies. His last Position was professor and Chairman of mathematics at the Rensselaer Polytechnic Institute Hartford Graduate Center. He was interested in most branches of mathematics at the Rensselaer polytechnic Institute, Hartford Graduate Center. He was interested in most branches of mathematics, especially those which involve applications to physics and engineering problems. He was the author of numerous journal articles and 14 books on various topics in mathematics.

John J. Schiller is an associate professor of mathematics at Temple University. He received his Ph.D. at the University of Pennsylvania.

R. Alu Srinivasan is a professor of mathematics at Temple University. He received his Ph.D. at Wayne State University and has published extensively in probability and statistics.

Murray R. Spiegel (deceased) received the M.S. degree in physics and the Ph.D. in mathematics from Cornell University. He had positions at Harvard University, Columbia University, Oak Ridge and Rensselaer Polytechnic Institute, and served as a mathematical consultant at several large companies. His last position was professor and chairman of Mathematics at the Rensselaer Polytechnic Institute, Hartford Graduate Center.



Alu Srinivasan is Professor of Mathematics at Temple University. He received an M.S. in statistics and a Ph.D. in Mathematics from Wayne State University, and was Chair of Temple's Mathematics Department from 1990 to 1998. His primary research interests are in applied and mathematical statistics, combinatorics and probability. He has published some seventy papers in these areas and has supervised a dozen Ph.D. dissertations in statistical inference and biostatistics.

Table of Contents

Part I: Probability
1. Basic Probability
2. Random Variables and Probability Distributions
3. Mathematical Expectation
4. Special Probability Distributions

Part II: Statistics
5. Sampling Theory
6. Estimation Theory
7. Tests of Hypotheses and Significance
8. Curve Fitting, Regression, and Correlation
9. Analysis of Variance
10. Nonparametric Tests

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