Introductory Statistics, Fifth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods.
Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that they are really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples.
Applications and examples refer to real-world issues, such as gun control, stock price models, vaccines and other health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others.
1. Chapter 1: Introduction to Statistics - p. 1 2. Chapter 2: Describing Data Sets - p. 19 3. Chapter 3: Using Statistics to Summarize Data Sets - p. 67 4. Chapter 4: Probability - p. 143 5. Chapter 5: Discrete Random Variables - p. 209 6. Chapter 6: Normal Random Variables - p. 271 7. Chapter 7: Distributions of Sampling Statistics - p. 301 8. Chapter 8: Estimation - p. 335 9. Chapter 9: Testing Statistical Hypotheses - p. 389 10. Chapter 10: Hypothesis Tests Concerning Two Populations - p. 443 11. Chapter 11: Analysis of Variance - p. 501 12. Chapter 12: Linear Regression - p. 535 13. Chapter 13: Chi-Squared Goodness-of-Fit Tests - p. 601 14. Chapter 14: Nonparametric Hypotheses Tests - p. 639 15. Chapter 15: Quality Control - p. 691 16. Chapter 16: Machine Learning and Big Data - p. 719 17. Appendix A: A Data Set - p. 737 18. Appendix B: Mathematical Preliminaries - p. 741 19. Answers to Odd-Numbered Problems - p. 743 20. Index - p. 787 21. Introductory Statistics - p. 795
Introductory Statistics, Fifth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods.
Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that they are really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples.
Applications and examples refer to real-world issues, such as gun control, stock price models, vaccines and other health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others.
1. Chapter 1: Introduction to Statistics - p. 1 2. Chapter 2: Describing Data Sets - p. 19 3. Chapter 3: Using Statistics to Summarize Data Sets - p. 67 4. Chapter 4: Probability - p. 143 5. Chapter 5: Discrete Random Variables - p. 209 6. Chapter 6: Normal Random Variables - p. 271 7. Chapter 7: Distributions of Sampling Statistics - p. 301 8. Chapter 8: Estimation - p. 335 9. Chapter 9: Testing Statistical Hypotheses - p. 389 10. Chapter 10: Hypothesis Tests Concerning Two Populations - p. 443 11. Chapter 11: Analysis of Variance - p. 501 12. Chapter 12: Linear Regression - p. 535 13. Chapter 13: Chi-Squared Goodness-of-Fit Tests - p. 601 14. Chapter 14: Nonparametric Hypotheses Tests - p. 639 15. Chapter 15: Quality Control - p. 691 16. Chapter 16: Machine Learning and Big Data - p. 719 17. Appendix A: A Data Set - p. 737 18. Appendix B: Mathematical Preliminaries - p. 741 19. Answers to Odd-Numbered Problems - p. 743 20. Index - p. 787 21. Introductory Statistics - p. 795
