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Overview
Used by hundreds of thousands of students since its first edition, INTRODUCTION TO PROBABILITY AND STATISTICS, 15th Edition, Metric Edition continues to blend the best of its proven, error-free coverage with new innovations. Written for the traditional Introductory Statistics course, the book takes advantage of modern technology--including computational software and graphing calculators--to facilitate statistical reasoning as well as the interpretation of statistical results. In addition to showing how to apply statistical procedures, the authors explain how to describe real sets of data meaningfully, what the statistical tests mean in terms of their practical applications, how to evaluate the validity of the assumptions behind statistical tests, and what to do when statistical assumptions have been violated. The new edition strives to simplify the language of the exposition, examples and exercises, while retaining the statistical integrity that has made this text a market leader--and builds upon this tradition of excellence with new technology integration.
- Expanded coverage: This edition includes expanded coverage of the uniform distribution, the exponential distribution and normal probability plots for assessing normality, with appropriate exercises. New topics include best subsets regression procedures and binary logistic regression.
- Technology integration: Technology Today features at the end of each chapter offer updated Microsoft Excel 2016 and MINITAB 18 outputs and instructions, giving students hands-on experience performing statistical analysis with these widely used programs. New sections in most chapters give students instructions for using the TI 83/84 Plus calculators to perform the necessary statistical analyses.
- Revamped exercise sets: The exercises have been scaffolded to help the learner move from more basic concepts to independent application of skills. New exercises have been introduced and dated exercises deleted, and exercises have been more evenly distributed throughout the chapter sections.
- Reader friendly: The language of the exposition, examples and exercises have been simplified, while still retaining the statistical integrity of the text.
- Student's t table: The Student’s t table (Table 4 in Appendix I) has been expanded to include more degrees of freedom (df = 1-40, 45, 50, 55, 60, 65, 60, 80, 90, 100, 200, 300, 400, 500).
- Discrete Probability Distributions: Section 4.8 (Discrete Random Variables and their Probability Distributions) has been moved to become Section 5.1 in Chapter 5 (renamed “Discrete Probability Distributions”).
- The Student’s t table (Table 4 in Appendix I) has been expanded to include more degrees of freedom (df = 1-40, 45, 50, 55, 60, 65, 60, 80, 90, 100, 200, 300, 400, 500)
- Section 4.8 (Discrete Random Variables and their Probability Distributions) has been moved to become Section 5.1 in Chapter 5 (renamed “Discrete Probability Distributions”)
- Real data: This text continues to set the standard for using authentic data sets, helping students see the connections between their studies and their lives.
- New and updated exercises: The book includes more than 1,300 exercises, many of which are new or updated for this edition. New topics for the book's chapter-ending case study exercises include ”Are Your Clothes Really Clean?”, “School Accountability: Are We Doing Better?” and “Amazon Headquarters II.”
- Instructor resources: The book’s website includes the Complete Solutions Manual, Technology Guides, Test banks, PowerPoint lecture slides, Image Library, and Data Sets.
- Integrity and quality: The integrity of the statistics and the quality of the examples and exercises keep this text in the bestseller category. Comprehensive in coverage, it delivers a more rigorous offering with traditional coverage of probability. Instructors and students alike appreciate its error-free material and exercises, and its clear exposition.
- Quick reference: At the end of each chapter, Key Concepts and Formulas sections provide quick reference for students, helping them ensure they are well prepared for assignments and tests.
1. Describing Data with Graphs.
2. Describing Data with Numerical Measures.
3. Describing Bivariate Data.
4. Probability.
5. Discrete Probability Distributions.
6. The Normal Probability Distribution.
7. Sampling Distributions.
8. Large-Sample Estimation.
9. Large-Sample Tests of Hypotheses.
10. Inference from Small Samples.
11. The Analysis of Variance.
12. Simple Linear Regression and Correlation.
13. Multiple Linear Regression Analysis.
14. Analysis of Categorical Data.
15. Nonparametric Statistics.
Appendix I: Tables.
Answers to Selected Exercises.