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The Tao of Statistics
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The Tao of Statistics
A Path to Understanding (With No Math)

Second Edition


March 2015 | 192 pages | SAGE Publications, Inc

This Second Edition of 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.


 
Acknowledgments
 
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
 
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
 
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 Regressions
 
40. Abundance - Multivariate Analysis
 
41. Differences - t Tests and Analysis of Variance
 
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

This Second Edition retains all the charm and conciseness which made the original so tremendously helpful, and even enjoyable to read. I would not hesitate to recommend it to any student struggling to comprehend statistics. The Tao of Statistics' key benefit lies in its ability to overcome the anxiety which numbers provoke for too many beginners, or even for those struggling with more advanced statistical methodologies. The succinct, single-focus chapters compel readers, by asking that they just understand the intent and usefulness of each aspect, and no more. Thus, it maintains focus on the individual components rather than allowing them to become overwhelmed by the whole. One might say the individual trees can be appreciated once fear of the dark forest is allayed.

Erica Watson-Currie
University of Southern California

"The Tao of Statistics: A Path to Understanding (With No Math) appears in its second edition to provide a user-friendly guide to statistics that explains what they mean, with a difference - there's no math involved. Most books are loaded with formulas; this is loaded with explanation. The basic concepts are covered with attention to how and why they are applied, offering important keys to understanding. This second edition adds new coverage of 'big data' and its impact and concepts, material contrasting it with 'small data', and discussions on missing data and more. The result is a pick for any interested in more than math formulas."

The California Bookwatch
Midwest Book Review

“'For most people, the concept of statistics begins as a shadowy mathematical nightmare....' The author opens his introduction to the second edition with these words, and undoubtedly many engaged in statistical research would agree.  Unfortunately, these persons sometimes find themselves gathering, processing, and interpreting data with a great sense of discomfort as they blindly follow a mathematical procedure without really understanding what the results actually mean.  Keller (president, Halcyon Research, Inc.) clearly has this audience in mind.  Purists may be startled by a statistics book without numbers, graphs, or formulas, but they should appreciate Keller’s brief, insightful discussions designed to clarify each of his fifty topics.  Especially helpful are illustrations of how a high school principal, a public health director, or a sociologist might use the concept at hand.  In some cases the author even explains why these individuals might not need a particular procedure at all, a refreshingly honest approach that reflects his sense of tao.  Of course, statistics without graphs or data is not realistic, but the user of statistics has to have a basic understanding of what is being accomplished and, in that sense, the author has definitely succeeded."

N. W. Schillow, Lehigh Carbon Community College
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Key features

NEW TO THIS EDITION:

  • Coverage of big data has been added to better address its impact on p-values and other key concepts.
  • New coverage of small data shows readers how to handle data with fewer data points than optimal.
  • New discussions of missing data enhance readers’ understanding of the topic.
  • Coverage of effect sizes has been added due to their emerging use in journals and Big Data reliance on them.
  • Examples are now more humanized to provide a clearer understanding of key concepts.

KEY FEATURES:

  • Basic statistics are covered in an accessible fashion without emphasizing computation.
  • The book is ideal for readers who do not consider themselves advanced at math, have little interest in computing statistics, or just want to understand them.
  • Each concept is presented via impressions from a verse, an illustration, and 300 to 900 words of text.

Sample Materials & Chapters

Impact-Effect Sized

Abundance-Big Data


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