Fundamentals of Biostatistics 8th Edition Rosner Solutions Manual

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Product Details:

• ISBN-10 ‏ : ‎ 130526892X
• ISBN-13 ‏ : ‎ 978-1305268920
• Author: Bernard Rosner

Table of contents:

1. Chapter 1: General Overview
2. Chapter 2: Descriptive Statistics
3. 2.1 Introduction
4. 2.2 Measures of Location
5. 2.3 Some Properties of the Arithmetic Mean
6. 2.4 Measures of Spread
7. 2.5 Some Properties of the Variance and Standard Deviation
8. 2.6 The Coefficient of Variation
9. 2.7 Grouped Data
10. 2.8 Graphic Methods
11. 2.9 Case Study 1: Effects of Lead Exposureon Neurological and Psychological Function in Children
12. 2.10 Case Study 2: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
13. 2.11 Obtaining Descriptive Statistics on the Computer
14. 2.12 Summary
15. Problems
16. Chapter 3: Probability
17. 3.1 Introduction
18. 3.2 Definition of Probability
19. 3.3 Some Useful Probabilistic Notation
20. 3.4 The Multiplication Law of Probability
21. 3.5 The Addition Law of Probability
22. 3.6 Conditional Probability
23. 3.7 Bayes’ Rule and Screening Tests
24. 3.8 Bayesian Inference
25. 3.9 ROC Curves
26. 3.10 Prevalence and Incidence
27. 3.11 Summary
28. Problems
29. Chapter 1: General Overview
30. Chapter 2: Descriptive Statistics
31. 2.1 Introduction
32. 2.2 Measures of Location
33. 2.3 Some Properties of the Arithmetic Mean
34. 2.4 Measures of Spread
35. 2.5 Some Properties of the Variance and Standard Deviation
36. 2.6 The Coefficient of Variation
37. 2.7 Grouped Data
38. 2.8 Graphic Methods
39. 2.9 Case Study 1: Effects of Lead Exposureon Neurological and Psychological Function in Children
40. 2.10 Case Study 2: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
41. 2.11 Obtaining Descriptive Statistics on the Computer
42. 2.12 Summary
43. Problems
44. Chapter 3: Probability
45. 3.1 Introduction
46. 3.2 Definition of Probability
47. 3.3 Some Useful Probabilistic Notation
48. 3.4 The Multiplication Law of Probability
49. 3.5 The Addition Law of Probability
50. 3.6 Conditional Probability
51. 3.7 Bayes’ Rule and Screening Tests
52. 3.8 Bayesian Inference
53. 3.9 ROC Curves
54. 3.10 Prevalence and Incidence
55. 3.11 Summary
56. Problems
57. Chapter 4: Discrete Probability Distributions
58. 4.1 Introduction
59. 4.2 Random Variables
60. 4.3 The Probability-Mass Function for a Discrete Random Variable
61. 4.4 The Expected Value of a Discrete Random Variable
62. 4.5 The Variance of a Discrete Random Variable
63. 4.6 The Cumulative-Distribution Function of a Discrete Random Variable
64. 4.7 Permutations and Combinations
65. 4.8 The Binomial Distribution
66. 4.9 Expected Value and Variance of the Binomial Distribution
67. 4.10 The Poisson Distribution
68. 4.11 Computation of Poisson Probabilities
69. 4.12 Expected Value and Variance of the Poisson Distribution
70. 4.13 Poisson Approximation to the Binomial Distribution
71. 4.14 Summary
72. Problems
73. 4.1 Introduction
74. 4.2 Random Variables
75. 4.3 The Probability-Mass Function for a Discrete Random Variable
76. 4.4 The Expected Value of a Discrete Random Variable
77. 4.5 The Variance of a Discrete Random Variable
78. 4.6 The Cumulative-Distribution Function of a Discrete Random Variable
79. 4.7 Permutations and Combinations
80. 4.8 The Binomial Distribution
81. 4.9 Expected Value and Variance of the Binomial Distribution
82. 4.10 The Poisson Distribution
83. 4.11 Computation of Poisson Probabilities
84. 4.12 Expected Value and Variance of the Poisson Distribution
85. 4.13 Poisson Approximation to the Binomial Distribution
86. 4.14 Summary
87. Problems

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