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by Murray R. Spiegel, John J. Schiller and R Alu Srinivasan

Edition: 2ND 00Copyright: 2000

Publisher: McGraw-Hill Publishing Company

Published: 2000

International: No

Murray R. Spiegel, John J. Schiller and R Alu Srinivasan

Edition: 2ND 00
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Schaum's Outline of Probability and Statistics, 2/e is an introduction to calculus-based statistics and probability, covering all the topics in statistics and probability courses directed to mathematics, natural-science, and engineering students. Probability theory supplies a methodology through which statistics can be used to draw conclusions on the basis of analysis of data like sampling theory, and prediction or forecasting. Since the text is calculus-based, it is above the level of elementary probability and statistics courses taken by a general college audience. It assumes a general familiarity with the subject matter, is geared mostly toward students in engineering or science majors.

**Schiller, John J. : Temple University**

John J. Schiller, is an Associate Professor of Mathematics at Temple University. He received his Ph.D. at the University of Pennsylvania and has published research papers in the areas of Riemann surfaces, discrete mathematics biology. He has also coauthored texts in finite mathematics, precalculus, and calculus.

**Part I: Probability.**

Chapter 1: Basic Probability.

Chapter 2: Random Variables and Probability Distributions.

Chapter 3: Mathematical Expectation.

Chapter 4: Special Probability Distributions.

**Part II: Statistics.**

Chapter 5: Sampling Theory.

Chapter 6: Estimation Theory.

Chapter 7: Tests of Hypotheses and Significance.

Chapter 8: Curve Fitting, Regression, and Correlation.

Chapter 9: Analysis of Variance.

Chapter 10: Nonparametric Tests.

Appendices.

Index.

Index for Solved Problems.

Summary

Schaum's Outline of Probability and Statistics, 2/e is an introduction to calculus-based statistics and probability, covering all the topics in statistics and probability courses directed to mathematics, natural-science, and engineering students. Probability theory supplies a methodology through which statistics can be used to draw conclusions on the basis of analysis of data like sampling theory, and prediction or forecasting. Since the text is calculus-based, it is above the level of elementary probability and statistics courses taken by a general college audience. It assumes a general familiarity with the subject matter, is geared mostly toward students in engineering or science majors.

Author Bio

**Schiller, John J. : Temple University**

John J. Schiller, is an Associate Professor of Mathematics at Temple University. He received his Ph.D. at the University of Pennsylvania and has published research papers in the areas of Riemann surfaces, discrete mathematics biology. He has also coauthored texts in finite mathematics, precalculus, and calculus.

Table of Contents

**Part I: Probability.**

Chapter 1: Basic Probability.

Chapter 2: Random Variables and Probability Distributions.

Chapter 3: Mathematical Expectation.

Chapter 4: Special Probability Distributions.

**Part II: Statistics.**

Chapter 5: Sampling Theory.

Chapter 6: Estimation Theory.

Chapter 7: Tests of Hypotheses and Significance.

Chapter 8: Curve Fitting, Regression, and Correlation.

Chapter 9: Analysis of Variance.

Chapter 10: Nonparametric Tests.

Appendices.

Index.

Index for Solved Problems.

Publisher Info

Publisher: McGraw-Hill Publishing Company

Published: 2000

International: No

Published: 2000

International: No

**Schiller, John J. : Temple University**

John J. Schiller, is an Associate Professor of Mathematics at Temple University. He received his Ph.D. at the University of Pennsylvania and has published research papers in the areas of Riemann surfaces, discrete mathematics biology. He has also coauthored texts in finite mathematics, precalculus, and calculus.

**Part I: Probability.**

Chapter 1: Basic Probability.

Chapter 2: Random Variables and Probability Distributions.

Chapter 3: Mathematical Expectation.

Chapter 4: Special Probability Distributions.

**Part II: Statistics.**

Chapter 5: Sampling Theory.

Chapter 6: Estimation Theory.

Chapter 7: Tests of Hypotheses and Significance.

Chapter 8: Curve Fitting, Regression, and Correlation.

Chapter 9: Analysis of Variance.

Chapter 10: Nonparametric Tests.

Appendices.

Index.

Index for Solved Problems.