Intuitive Biostatistics pdf epub mobi txt 电子书 下载 2025

想要找书就要到 图书目录大全

立刻按 ctrl+D收藏本页

你会得到大惊喜!!

Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: 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. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists. NEW TO THIS EDITION: * Chapter 1 shows how our intuitions lead us to misinterpret data, thus explaining the need for statistical rigor. * Chapter 11 explains the lognormal distribution, an essential topic omitted from many other statistics books. * Chapter 21 contrasts testing for equivalence with testing for differences. * Chapters 22, 23, and 40 explore the pervasive problem of multiple comparisons. * Chapters 24 and 25 review testing for normality and outliers. * Chapter 35 shows how statistical hypothesis testing can be understood as comparing the fits of alternative models. * Chapters 37 and 38 provide a brief introduction to multiple, logistic, and proportional hazards regression. * Chapter 46 reviews one example in great depth, reviewing numerous statistical concepts and identifying common mistakes. * Chapter 47 includes 49 multi-part problems, with answers fully discussed in Chapter 48. * New "Q and A" sections throughout the book review key concepts.

CONTENTS
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
· · · · · · (收起)