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Part A: Introducing Statistics

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. Comparing Groups with Confidence Intervals and P Values

18. Interpreting a Result That Is Statistically Significant

20. Statistical Power

21. Testing for Equivalence or Noninferiority

PART E: Challenges in Statistics

23. The Ubiquity of Multiple Comparisons

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 Operating 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. Statistics and Reproducibility

48. Checklists for Reporting Statistical Methods and Results