Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition

Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition [Paperback]

Author: Harvey Motulsky | Language: English | ISBN: 0199946647 | Format: PDF, EPUB

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• Book Details
• Table of Contents
• Reviews

Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition
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Thoroughly revised and updated, the third edition of Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking retains and refines the core perspectives of the previous editions: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes.

With its engaging and conversational tone, this unique book provides a clear introduction to statistics for undergraduate and graduate students in a wide range of fields and also serves as a statistics refresher for working scientists. It is especially useful for those students in health-science related fields who have no background in biostatistics.

CONTENTS

Part A: Introducing Statistics 

 1. Statistics and Probability Are Not Intuitive

 2. The Complexities of Probability

 3. From Sample to Population 

Part B: Confidence Intervals 

 4. Confidence Interval of a Proportion 

 5. Confidence Interval of Survival Data 

 6. Confidence Interval of Counted Data 

Part C: Continuous Variables 

 7. Graphing Continuous Data

 8. Types of Variables 

 9. Quantifying Scatter 

10. The Gaussian Distribution 

11. The Lognormal Distribution and Geometric Mean

12. Confidence Interval of a Mean 

13. The Theory of Confidence Intervals

14. Error Bars 

PART D: P Values and Significance 

15. Introducing P Values 

16. Statistical Significance and Hypothesis Testing

17. Relationship Between Confidence Intervals and Statistical Significance 

18. Interpreting a Result That Is Statistically Significant 

19. Interpreting a Result That Is Not Statistically Significant 

20. Statistical Power

21. Testing for Equivalence or Noninferiority

PART E: Challenges in Statistics 

22. Multiple Comparisons Concepts 

23. The Ubiquity of Multiple Comparison

24. Normality Tests

25. Outliers 

26. Choosing a Sample Size

PART F: Statistical Tests 

27. Comparing Proportions

28. Case-Control Studies

29. Comparing Survival Curves 

30. Comparing Two Means: Unpaired t Test

31. Comparing Two Paired Groups

32. Correlation 

PART G: Fitting Models to Data 

33. Simple Linear Regression

34. Introducing Models 

35. Comparing Models 

36. Nonlinear Regression

37. Multiple Regression 

38. Logistic and Proportional Hazards Regression

PART H The Rest of Statistics 

39. Analysis of Variance 

40. Multiple Comparison Tests After ANOVA 

41. Nonparametric Methods

42. Sensitivity and Specificity and Receiver-Operator Characteristic Curves 

43. Meta-analysis

PART I Putting It All Together 

44. The Key Concepts of Statistics

45. Statistical Traps to Avoid

46. Capstone Example 

47. Review Problems 

48. Answers to Review Problems 

 

Direct download links available for Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition [Paperback]

• Paperback: 576 pages
• Publisher: Oxford University Press; 3rd edition (December 13, 2013)
• Language: English
• ISBN-10: 0199946647
• ISBN-13: 978-0199946648
• Product Dimensions: 9.2 x 6.1 x 1 inches
• Shipping Weight: 1.6 pounds (View shipping rates and policies)
• Amazon Best Sellers Rank: #13,662 in Books (See Top 100 in Books)
  • #3 in Books > Medical Books > Basic Sciences > Biostatistics
  • #3 in Books > Textbooks > Medicine & Health Sciences > Research > Biostatistics
  • #36 in Books > Textbooks > Science & Mathematics > Mathematics > Statistics

This is a fantastic book. It is well written and enjoyable to read. I bought it to complement Fundamentals of Biostatistics by Rosner I was reading at the time. This is the book you need to read if you want to understand the "why", but not necessarily the "how" behind different statistical approaches or if you want to be able to interpret the results of a statistical analysis.

By Natalie D. Fedorova

For over a decade, I have been searching for a clear, lucid guide to statistics that I can use in my research and share with my students. Finally, after combing through dozens of books, I can say I found an excellent book.

Harvey Motulsky seems to have pulled off the trick of writing a book with high explanatory power that will not intimidate the busy undergraduate, graduate student, postdoc, or primary investigator who wants to learn the necessary information but does not want to drown in esoteric details, problem sets, or unhelpful information. As a practicing neuroscientist, I appreciate a guide that is informative but also a pleasure to read (I don't have time to read through the standard statistic texts I have come across).

It is not surprising that Motulsky is also the CEO of GraphPad Software, the company that makes Prism. This software intuitively guides scientists into using the appropriate statistical tests for their data, and it is easily the best and most user-friendly statistical software on the market. I have used Prism for years and was unaware that Motulsky also wrote this book. Now I plan on recommending this book to my students and colleagues, and I purchased a copy for my office and lab.

If you are a bioscientist intimidated by statistics (or feel like you could use a refresher after a long ago forgotten stats class), this book is a gem.

By Matt Carter

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