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Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition from Oxford University Press, USA

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Product Description

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Manufacturer Description

Extensively modified and updated, the 3rd edition of Intuitive Biostatistics: A Nonmathematical Overview of Statistical Thinking maintains and refines the core perspectives of the previous editions: a concentrate on ways to translate statistical outcomes instead of on ways to analyze data, minimal usage of equations, and a comprehensive evaluation of presumptions and common mistakes.

With its appealing and conversational tone, this distinct book offers a clear intro to statistics for undergraduate and graduate students in a wide range of fields and also functions as a stats refresher for working experts. It is particularly helpful for those students in health-science related fields who have no background in biostatistics.


Part A: Presenting Data
1. Data and Chance Are Not User-friendly
2. The Complexities of Chance
3. From Sample to Populace
Part B: Self-confidence Intervals
4. Self-confidence Period of a Proportion
5. Self-confidence Period of Survival Data
6. Self-confidence Period of Counted Data
Part C: Continuous Variables
7. Graphing Continuous Data
8. Kinds of Variables
9. Quantifying Scatter
10. The Gaussian Circulation
11. The Lognormal Circulation and Geometric Mean
12. Self-confidence Period of a Mean
13. The Concept of Self-confidence Intervals
14. Error Bars
PART D: P Values and Importance
15. Presenting P Values
16. Statistical Importance and Hypothesis Testing
17. Relationship Between Self-confidence Intervals and Statistical Importance
18. Interpreting a Result That Is Statistically Substantial
19. Interpreting a Result That Is Not Statistically Substantial
20. Statistical Power
21. Testing for Equivalence or Noninferiority
PART E: Challenges in Data
22. Multiple Comparisons Concepts
23. The Universality of Multiple Comparison
24. Normality Tests
25. Outliers
26. Selecting a Sample Size
PART F: Statistical Tests
27. Comparing Proportions
28. Case-Control Researches
29. Comparing Survival Curves
30. Comparing Two Methods: Unpaired t Test
31. Comparing Two Paired Groups
32. Connection
PART G: Fitting Models to Data
33. Simple Linear Regression
34. Presenting Models
35. Comparing Models
36. Nonlinear Regression
37. Multiple Regression
38. Logistic and Proportional Hazards Regression
PART H The Rest of Data
39. Analysis of Difference
40. Multiple Comparison Tests After ANOVA
41. Nonparametric Methods
42. Sensitivity and Uniqueness and Receiver-Operator Feature Curves
43. Meta-analysis
PART I Putting It All Together
44. The Secret Concepts of Data
45. Statistical Traps to Avoid
46. Capstone Example
47. Testimonial Problems
48. Responses to Testimonial Problems

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