Intuitive Biostatistics : A Nonmathematical Guide to Statistical Thinking （4TH）

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Intuitive Biostatistics : A Nonmathematical Guide to Statistical Thinking （4TH）

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  • 製本 Paperback:紙装版/ペーパーバック版／ページ数 568 p.
  • 言語 ENG
  • 商品コード 9780190643560
  • DDC分類 610.727

Full Description


Intuitive Biostatistics takes a non-technical, non-quantitative approach to statistics and emphasizes interpretation of statistical results rather than the computational strategies for generating statistical data. This makes the text especially useful for those in health-science fields who have not taken a biostatistics course before. The text is also an excellent resource for professionals in labs, acting as a conceptually oriented and accessiblebiostatistics guide. With an engaging and conversational tone, Intuitive Biostatistics provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists.

Contents

Part A. Introducing Statistics1. Statistics and Probability are not Intuitive2. The Complexities of Probability3. From Sample to PopulationPart B. Introducing Confidence Intervals4. Confidence Interval of a Proportion5. Confidence Interval of Survival Data6. Confidence Interval of Counted Data (Poisson Distribution)Part C. Continuous Variables7. Graphing Continuous Data8. Types of Variables9. Quantifying Scatter10. The Gaussian Distribution11. The Lognormal Distribution and Geometric Mean12. Confidence Interval of a Mean13. The Theory of Confidence Intervals14. Error BarsPart D. P Values and Statistical Significance15. Introducing P Values16. Statistical Significance and Hypothesis Testing17. Comparing Groups with Confidence Intervals and P Values18. Interpreting a Result That Is Statistically Significant19. Interpreting a Result That Is Not Statistically Significant20. Statistical Power21. Testing For Equivalence or NoninferiorityPart E. Challenges in Statistics22. Multiple Comparisons Concepts23. The Ubiquity of Multiple Comparisons24. Normality Tests25. Outliers26. Choosing a Sample SizePart F. Statistical Tests27. Comparing Proportions28. Case-Control Studies29. Comparing Survival Curves30. Comparing Two Means: Unpaired t Test31. Comparing Two Paired Groups32. CorrelationPart G. Fitting Models to Data33. Simple Linear Regression34. Introducing Models35. Comparing Models36. Nonlinear Regression37. Multiple Regression38. Logistic and Proportional Hazards RegressionPart H. The Rest of Statistics39. Analysis of Variance40. Multiple Comparison Tests after ANOVA41. Nonparametric Methods42. Sensitivity, Specificity, and Receiver-Operating Characteristic Curves43. Meta-AnalysisPart I. Putting It All Together44. The Key Concepts of Statistics45. Statistical Traps to Avoid46. Capstone Example47. Statistics and Reproducibility48. Checklists for Reporting Statistical Methods and ResultsPart J. Appendices