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Main description:
In this revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. To quote from the preface, "It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data." Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.
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Produktbeschreibung
Main description:
In this revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. To quote from the preface, "It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data." Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.

- Ross's clear writing style leads students easily through descriptive and inferential statistics
- Hundreds of exercises assess students' conceptual and computational understanding
- Real data sets from current issues draw from a variety of disciplines
- Statistics in Perspective highlights demonstrate real-world application of techniques and concepts
- Historical Perspectives sections profile prominent statisticians and events
- Chapter Introductions pose realistic statistical situations
- Chapter Summaries and Key Terms reinforce learning
- A detachable Formula Card includes frequently used tables and formulas to facilitate studying
- Enclosed CD-ROM contains programs that can be used to solve basic computation problems

New in this Edition:
- Dozens of new and updated examples and exercises
- New sections on: assessing the linear regression model by analyzing residuals; quality control; counting principles; Poisson random variables
- Detailed edits and enhancements based on users' feedback
- A computerized test bank, plus updates to other ancillaries

Ancillaries:
- Instructor's Manual
- Student Solutions Manual (ISBN: 0120885514)
- Printed Test Bank
- Computerized Test Bank
- Instructors web site with additional online materials

Review quote:
"This is an excellent text. Possibly the best introductory text I have ever taught out of and I have been teaching Introductory Statistics since 1979. I have been using the book for the last three years and cannot think of any reason why I would ever switch to another text. "
- Vincent Lariccia, University of Delaware

Ross has done an outstanding job in the number and quality of his exercises. The examples are realistic, stimulating and cover a wide variety of practical situations. Ross is a master in clear and concise expositionhis style will appeal to students taking their first course in Statistics. I would definitely recommend adoption.

- John Deely, Purdue University

Table of contents:
Preface
Introduction to Statistics
Describing Data Sets
Using Statistics to Summarize Data Sets
Probability
Discrete Random Variables
Normal Random Variables
Distributions of Sampling Statistics
Estimation
Testing Statistical Hypotheses
Hypothesis Tests Concerning Two Populations
Analysis of Variance
Linear Regression
Chi-Squared Goodness of Fit Tests
Nonparametric Hypotheses Tests
Quality Control
Appendices
Autorenporträt
Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.