The Tao of Statistics

The Tao of Statistics
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Описание книги

This Second Edition of Dana K. Keller’s The Tao of Statistics: A Path to Understanding (With No Math) provides a reader-friendly approach to statistics in plain English. Unlike other statistics books, this text explains what statistics mean and how they are used, rather than how to calculate them. The book walks readers through basic concepts as well as some of the most complex statistical models in use. The Second Edition adds coverage of big data to better address its impact on p-values and other key concepts; material on small data to show readers how to handle data with fewer data points than optimal; and other new topics like missing data and effect sizes. The book’s two characters (a high school principal and a director of public health) return in the revised edition, with their examples expanded and updated with reference to contemporary concerns in the fields of education and health.

Оглавление

Dana K. Keller. The Tao of Statistics

The Tao of Statistics

The Tao of Statistics

Contents

Acknowledgments

About the Illustrator

About the Author

Introduction to the Second Edition

1. The Beginning — The Question

2. Ambiguity—Statistics

3. Fodder—Data

4. Data—Measurement

5. Data Structure—Levels of Measurement

5.A. Nominal

5.B. Ordinal

5.C. Interval

5.D. Ratio

6. Simplifying—Groups and Clusters

7. Counts—Frequencies

8. Pictures—Graphs

9. Scatterings—Distributions

10. Bell-Shaped—The Normal Curve

11. Lopsidedness—Skewness

12. Averages—Central Tendencies

12.A. Mean

12.B. Median

12.C. Mode

13. Two Types—Descriptive and Inferential

14. Foundations—Assumptions

15. Murkiness—Missing Data

16. Leeway—Robustness

17. Consistency—Reliability

18. Truth—Validity

19. Unpredictability—Randomness

20. Representativeness—Samples

21. Mistakes—Error

22. Real or Not—Outliers

23. Impediments—Confounds

24. Nuisances—Covariates

25. Background—Independent Variables

26. Targets—Dependent Variables

27. Inequality—Standard Deviations and Variance

28. Prove—No, Falsify

29. No Difference—The Null Hypothesis

30. Reductionism—Models

31. Risk—Probability

32. Uncertainty—p Values

33. Expectations—Chi-Square

34. Importance vs. Difference—Substantive vs. Statistical Significance

35. Strength—Power

36. Impact—Effect Sizes

37. Likely Range—Confidence Intervals

38. Association—Correlation

39. Predictions—Multiple Regression

40. Abundance—Multivariate Analysis

41. Differences—t Tests and Analysis of Variance

41.A. ANOVA

41.B. ANCOVA

41.C. MANOVA

41.D. MANCOVA

42. Differences That Matter—Discriminant Analysis

43. Both Sides Loaded—Canonical Covariance Analysis

44. Nesting—Hierarchical Models

45. Cohesion—Factor Analysis

46. Ordered Events—Path Analysis

47. Digging Deeper—Structural Equation Models

48. Abundance—Big Data

49. Scarcity—Small Data

50. Fiddling—Modifications and New Techniques

51. Epilogue

Отрывок из книги

Second Edition

Second Edition

.....

This journey is about living a series of experiences, their impressions, and sometimes even their emotions. These experiences lead to a deeper understanding of the world of statistics as we follow the paths of two research-oriented professionals with different careers as they experience the statistical concepts presented herein. Try to experience the concepts with them. Stroll down the path together. Before beginning, though, a few thoughts on statistics themselves might be helpful.

This journey is best experienced in comfortable clothing, in a favorite chair, and in a quiet space.

.....

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