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by Richard Deveaux, Paul Velleman and David Bock

Edition: 05Copyright: 2005

Publisher: Addison-Wesley Longman, Inc.

Published: 2005

International: No

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This book is written for the introductory statistics course and students majoring in any field. It is written in an approachable, informal style that invites students to think about how to reason when data is available. Stats: Data and Models (SDM), as compared to Intro Stats, offers Math Boxes, which present the mathematical underpinnings of the statistical methods and concepts, and advanced topics (Ch. 28-31) that are often covered in a two-semester course, plus the inclusion of non-parametrics. SDM carries a core focus on statistical thinking and understanding analyses throughout the text, emphasizing how statistics helps us to understand the world. The book also recognizes the central role that technology plays in statistics. SDM is organized into short teachable chapters that focus on one topic at a time, offering instructors flexibility in selecting topics while students receive digestible chunks of information that build on previous material before moving on.

Features

- Math Boxes: Offered in most chapters, students will find the mathematical underpinnings of the statistical methods and concepts called out in Math Boxes throughout the text. Set apart from the narrative, math boxes provide the proofs, derivations, and justifications so that students may refer to the underlying mathematics for greater depth.
- Think, Show, Tell: The mantra of Think, Show, and Tell is repeated in EVERY chapter and used to illustrate worked examples. "Think," emphasizes the importance of thinking about a statistics question, asking What do we know? What do we hope to learn? Are the assumptions and conditions satisfied? "Show" holds the mechanics of calculating results -- something for which the technology is relied upon whenever possible. The "Tell" step reports the findings and explains the results as a clear account of what has been learned.
- Step-By-Step Examples: Each chapter has step-by-step examples. These examples work through a complete solution to a statistics problem, illustrating an ideal or model student response (including Think, Show, and Tell steps) and commenting on it in an adjacent column.
- What Can Go Wrong?: Each chapter includes a discussion of common misuses, misapplications, and misunderstanding of statistics to help students recognize and avoid them. The slander that "you can prove anything with statistics" arises from the misuse of statistical methods. This book arms students with the weapons to detect statistical error and debunk misuses of statistics.

I. Exploring and Understanding Data

1. Stats Starts Here

2. Data

3. Displaying Categorical Data

4. Displaying Quantitative Data

5. Describing Distributions Numerically

6. The Standard Deviation as a Ruler and the Normal Model

II. Exploring Relationships between Variables

7. Scatterplots, Association, and Correlation

8. Linear Regression

9. Regression Wisdom

10. Re-Expressing Data: It's easier than you think

III. Gathering Data

11. Understanding Randomness

12. Sample Surveys

13. Experiments

IV. Randomness and Probability

14. From Randomness to Probability

15. Probability Rules!

16. Random Variables

17. Probability Models

V. From The Data at Hand to the World at Large

18. Sampling Distribution Models

19. Confidence Intervals for Proportions

20. Testing Hypotheses about Proportions

21. More About Tests

22. Comparing Two Proportions

VI. Learning About the World

23. Inferences About Means

24. Comparing Means

25. Paired Samples and Blocks

VII. Modeling the World

26. Inferences for Regression

27. Analysis of Variance

28. Two Way Analysis of Variance

29. Multiple Regression

30. Multiple Regression Wisdom

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Summary

This book is written for the introductory statistics course and students majoring in any field. It is written in an approachable, informal style that invites students to think about how to reason when data is available. Stats: Data and Models (SDM), as compared to Intro Stats, offers Math Boxes, which present the mathematical underpinnings of the statistical methods and concepts, and advanced topics (Ch. 28-31) that are often covered in a two-semester course, plus the inclusion of non-parametrics. SDM carries a core focus on statistical thinking and understanding analyses throughout the text, emphasizing how statistics helps us to understand the world. The book also recognizes the central role that technology plays in statistics. SDM is organized into short teachable chapters that focus on one topic at a time, offering instructors flexibility in selecting topics while students receive digestible chunks of information that build on previous material before moving on.

Features

- Math Boxes: Offered in most chapters, students will find the mathematical underpinnings of the statistical methods and concepts called out in Math Boxes throughout the text. Set apart from the narrative, math boxes provide the proofs, derivations, and justifications so that students may refer to the underlying mathematics for greater depth.
- Think, Show, Tell: The mantra of Think, Show, and Tell is repeated in EVERY chapter and used to illustrate worked examples. "Think," emphasizes the importance of thinking about a statistics question, asking What do we know? What do we hope to learn? Are the assumptions and conditions satisfied? "Show" holds the mechanics of calculating results -- something for which the technology is relied upon whenever possible. The "Tell" step reports the findings and explains the results as a clear account of what has been learned.
- Step-By-Step Examples: Each chapter has step-by-step examples. These examples work through a complete solution to a statistics problem, illustrating an ideal or model student response (including Think, Show, and Tell steps) and commenting on it in an adjacent column.
- What Can Go Wrong?: Each chapter includes a discussion of common misuses, misapplications, and misunderstanding of statistics to help students recognize and avoid them. The slander that "you can prove anything with statistics" arises from the misuse of statistical methods. This book arms students with the weapons to detect statistical error and debunk misuses of statistics.

Table of Contents

I. Exploring and Understanding Data

1. Stats Starts Here

2. Data

3. Displaying Categorical Data

4. Displaying Quantitative Data

5. Describing Distributions Numerically

6. The Standard Deviation as a Ruler and the Normal Model

II. Exploring Relationships between Variables

7. Scatterplots, Association, and Correlation

8. Linear Regression

9. Regression Wisdom

10. Re-Expressing Data: It's easier than you think

III. Gathering Data

11. Understanding Randomness

12. Sample Surveys

13. Experiments

IV. Randomness and Probability

14. From Randomness to Probability

15. Probability Rules!

16. Random Variables

17. Probability Models

V. From The Data at Hand to the World at Large

18. Sampling Distribution Models

19. Confidence Intervals for Proportions

20. Testing Hypotheses about Proportions

21. More About Tests

22. Comparing Two Proportions

VI. Learning About the World

23. Inferences About Means

24. Comparing Means

25. Paired Samples and Blocks

VII. Modeling the World

26. Inferences for Regression

27. Analysis of Variance

28. Two Way Analysis of Variance

29. Multiple Regression

30. Multiple Regression Wisdom

Publisher Info

Publisher: Addison-Wesley Longman, Inc.

Published: 2005

International: No

Published: 2005

International: No

This book is written for the introductory statistics course and students majoring in any field. It is written in an approachable, informal style that invites students to think about how to reason when data is available. Stats: Data and Models (SDM), as compared to Intro Stats, offers Math Boxes, which present the mathematical underpinnings of the statistical methods and concepts, and advanced topics (Ch. 28-31) that are often covered in a two-semester course, plus the inclusion of non-parametrics. SDM carries a core focus on statistical thinking and understanding analyses throughout the text, emphasizing how statistics helps us to understand the world. The book also recognizes the central role that technology plays in statistics. SDM is organized into short teachable chapters that focus on one topic at a time, offering instructors flexibility in selecting topics while students receive digestible chunks of information that build on previous material before moving on.

Features

- Math Boxes: Offered in most chapters, students will find the mathematical underpinnings of the statistical methods and concepts called out in Math Boxes throughout the text. Set apart from the narrative, math boxes provide the proofs, derivations, and justifications so that students may refer to the underlying mathematics for greater depth.
- Think, Show, Tell: The mantra of Think, Show, and Tell is repeated in EVERY chapter and used to illustrate worked examples. "Think," emphasizes the importance of thinking about a statistics question, asking What do we know? What do we hope to learn? Are the assumptions and conditions satisfied? "Show" holds the mechanics of calculating results -- something for which the technology is relied upon whenever possible. The "Tell" step reports the findings and explains the results as a clear account of what has been learned.
- Step-By-Step Examples: Each chapter has step-by-step examples. These examples work through a complete solution to a statistics problem, illustrating an ideal or model student response (including Think, Show, and Tell steps) and commenting on it in an adjacent column.
- What Can Go Wrong?: Each chapter includes a discussion of common misuses, misapplications, and misunderstanding of statistics to help students recognize and avoid them. The slander that "you can prove anything with statistics" arises from the misuse of statistical methods. This book arms students with the weapons to detect statistical error and debunk misuses of statistics.

1. Stats Starts Here

2. Data

3. Displaying Categorical Data

4. Displaying Quantitative Data

5. Describing Distributions Numerically

6. The Standard Deviation as a Ruler and the Normal Model

II. Exploring Relationships between Variables

7. Scatterplots, Association, and Correlation

8. Linear Regression

9. Regression Wisdom

10. Re-Expressing Data: It's easier than you think

III. Gathering Data

11. Understanding Randomness

12. Sample Surveys

13. Experiments

IV. Randomness and Probability

14. From Randomness to Probability

15. Probability Rules!

16. Random Variables

17. Probability Models

V. From The Data at Hand to the World at Large

18. Sampling Distribution Models

19. Confidence Intervals for Proportions

20. Testing Hypotheses about Proportions

21. More About Tests

22. Comparing Two Proportions

VI. Learning About the World

23. Inferences About Means

24. Comparing Means

25. Paired Samples and Blocks

VII. Modeling the World

26. Inferences for Regression

27. Analysis of Variance

28. Two Way Analysis of Variance

29. Multiple Regression

30. Multiple Regression Wisdom