---
product_id: 1700701
title: "Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition"
price: "£3.06"
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---

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

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- **What is this?** Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition
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## Description

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 Mean12. Confidence Interval of a Mean 13. The Theory of Confidence Intervals14. Error Bars PART D: P Values and Significance 15. Introducing P Values 16. Statistical Significance and Hypothesis Testing17. 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 Power21. Testing for Equivalence or Noninferiority PART E: Challenges in Statistics 22. Multiple Comparisons Concepts 23. The Ubiquity of Multiple Comparison24. Normality Tests25. Outliers 26. Choosing a Sample Size PART F: Statistical Tests 27. Comparing Proportions28. Case-Control Studies29. Comparing Survival Curves 30. Comparing Two Means: Unpaired t Test31. Comparing Two Paired Groups32. Correlation PART G: Fitting Models to Data 33. Simple Linear Regression34. Introducing Models 35. Comparing Models 36. Nonlinear Regression37. 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 Methods42. Sensitivity and Specificity and Receiver-Operator Characteristic Curves 43. Meta-analysis PART I Putting It All Together 44. The Key Concepts of Statistics45. Statistical Traps to Avoid46. Capstone Example 47. Review Problems 48. Answers to Review Problems

Review: An excellent statistics book - 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.
Review: This is the best introductory book on statistics I have read - This is the best introductory book on statistics I have read. It is written for people who need to make sense of papers containing statistical reports, or for non-statisticians who conduct simple statistical analyses themselves. It covers a broad range of statistical procedures that are widely used in biomedical research. A particularly nice feature is the careful, clear explanations of how to interpret p values, confidence intervals and (unusually for an introductory textbook) false discovery rates. You won't find clearer explanations than those provided here! The book is full of sensible advice. I highly recommend it for graduate research students and researchers who need a basic, working understanding of statistics.

## Features

- Used Book in Good Condition

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #211,394 in Books ( See Top 100 in Books ) #3 in Biostatistics (Books) #56 in Biology (Books) |
| Customer Reviews | 4.5 out of 5 stars 94 Reviews |

## Images

![Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition - Image 1](https://m.media-amazon.com/images/I/91Cfh+e+RPL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ An excellent statistics book
*by M***R on January 24, 2014*

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.

### ⭐⭐⭐⭐⭐ This is the best introductory book on statistics I have read
*by A***R on December 20, 2016*

This is the best introductory book on statistics I have read. It is written for people who need to make sense of papers containing statistical reports, or for non-statisticians who conduct simple statistical analyses themselves. It covers a broad range of statistical procedures that are widely used in biomedical research. A particularly nice feature is the careful, clear explanations of how to interpret p values, confidence intervals and (unusually for an introductory textbook) false discovery rates. You won't find clearer explanations than those provided here! The book is full of sensible advice. I highly recommend it for graduate research students and researchers who need a basic, working understanding of statistics.

### ⭐⭐⭐⭐⭐ An unequivocally insightful approach to biostatistics
*by R***D on March 5, 2016*

Intuitive biostatistics is a comprehensive overview of biostatistics. Instead of reading cover to cover, I have used this relatively detailed statistics text to review relevant sections as needed. Motulsky does not include mathematical equations. Rather, he focuses on interpreting statistical concepts, common pitfalls, and challenges the reader to think critically. Highly recommended for clinical, medical, and pharmaceutical professionals responsible for reviewing clinical data. Even for readers confident in their statistics knowledge, this is a great refresher. I have expanded my biostatistics acumen thanks to this book. This text is daily my go-to reference guide.

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*Last updated: 2026-06-21*