Schaum's Outlines Probability and Statistics

The ideal review for your probability and statistics course More than 40 million students have trusted Schaum's Outlines for their expert knowledge and helpful solved problems. Written by renowned experts in this field, "Schaum's Outline of Probability and Statistics" covers what you need to know for your course and, more important, your exams. Step-by-step, the authors walk you through coming up with solutions to exercises in this topic. 760 fully-worked problems solved step-by-step Hundreds of additional practice problems with answers Coverage of all course fundamentals Easy to understand methodology Clear, concise explanations of all probability and statistics concepts Appropriate for the following courses: introduction to probability & statistics, probability, business statistics, basic statistics, and beginning statistics Easily understood review of basic probability and statistics principles Supports all the major textbooks for the introductory probability and statistics course

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.

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