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

Feature

Used Book in Good Condition

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 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 SampleSize

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 HazardsRegression

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