Intuitive Biostatistics

 

Title: Intuitive Biostatistics

Edition: 2 (Completely revised)
Author: Harvey J. Motulsky
Publisher: Oxford University Press
Format: Paperback,  512 pages
Publication date: Jan. 2010 

ISBN13: 978-0199730063
ISBN10:  0199730067

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Part A: Introducing Statistics 

1. Statistics and Probability Are Not Intuitive 3

2. Why Statistics Can Be Hard to Learn 14

3. From Sample to Population 17

Part B: Confidence Intervals 

4. Confidence Interval of a Proportion 25

5. Confidence Interval of Survival Data 38

6. Confidence Interval of Counted Data 47

Part C: Continuous Variables 

7. Graphing Continuous Data 57

8. Types of Variables 67

9. Quantifying Scatter 71

10. The Gaussian Distribution 78

11. The Lognormal Distribution and Geometric Mean 83

12. Confidence Interval of a Mean 87

13. The Theory of Confidence Intervals 96

14. Error Bars 103

PART D: P Values and Significance 

15. Introducing P Values 111

16. Statistical Significance and Hypothesis Testing 122

17. Relationship Between Confidence Intervals and Statistical Significance 130

18. Interpreting a Result That Is Statistically Significant 134

19. Interpreting a Result That Is Not Statistically Significant 141

20. Statistical Power 146

21. Testing for Equivalence or Noninferiority 150

PART E: Challenges in Statistics 

22. Multiple Comparisons Concepts 159

23. Multiple Comparison Traps 168

24. Gaussian or Not? 175

25. Outliers 181

PART F: Statistical Tests 

26. Comparing Observed and Expected Distributions 191

27. Comparing Proportions: Prospective and Experimental Studies 196

28. Comparing Proportions: Case–Control Studies 203

29. Comparing Survival Curves 210

30. Comparing Two Means: Unpaired t Test 219

31. Comparing Two Paired Groups 231

32. Correlation 243

PART G: Fitting Models to Data 

33. Simple Linear Regression 255

34. Introducing Models 270

35. Comparing Models 276

36. Nonlinear Regression 285

37. Multiple, Logistic, and Proportional Hazards Regression 296

38. Multiple Regression Traps 315

PART H The Rest of Statistics 321

39. Analysis of Variance 323

40. Multiple Comparison Tests After ANOVA 331

41. Nonparametric Methods 344

42. Sensitivity and Specificity and Receiver-Operator Characteristic Curves 354

43. Sample Size 363

PART I Putting It All Together 375

44. Statistical Advice  377

45. Choosing a Statistical Test  387

46. Capstone Example 390

47. Review Problems 406

48. Answers to Review Problems 418

Appendices 

A. Statistics With GraphPad 451

B. Statistics With Excel 456

C. Statistics With R 458

D. Values of the t Distribution Needed to Compute CIs 460

E. A Review of Logarithms 462

References 465