Wednesday, 1 January 2014

PDF⋙ Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition by Harvey Motulsky

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

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

Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition by Harvey Motulsky PDF, ePub eBook D0wnl0ad

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 
 


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