Complete Solution Manual Fundamentals of Biostatistics 8th Edition
Author:Rosner All Chapters
,CONTENTS
Preface, Vii
CHAPTER 1 General Overview 1
There Are No Problems/Solutions In Chapter 1 Of The Textbook.
CHAPTER 2 Descriptive Statistics 2
Review Of Key Concepts, 2 2.2.2 Quasi-Range, 6
2.1 Measures Of Location, 2 2.2.3 Standard Deviation, Variance, 7
2.1.1 Arithmetic Mean, 2 2.2.4 Coefficient Of Variation (CV), 8
2.1.2 Median, 3 2.3 Some Other Methods For Describing Data, 8
2.1.3 Stem-And-Leaf Plots, 2.3.1 Frequency Distribution, 8
3 2.3.2 Box Plot, 8
2.1.4 Percentiles, 4 Problems, 9
2.1.5 Geometric Mean, 5 Solutions, 10
2.2 Measures Of Spread, 6 Reference, 11
2.2.1 Range, 6
CHAPTER 3 Probability 12
Review Of Key Concepts, 12 3.6 Sensitivity, Specificity, Predictive Values
3.1 Frequency Definition Of Probability, 12 OfScreening Tests, 15
3.2 Multiplication Law Of Probability, 13 3.6.1 ROC Curves, 16
3.3 Addition Law Of Probability, 13 3.7 Bayes’ Theorem, 17
3.4 Conditional Probability, 13 Problems, 18
3.4.1 Relative Risk, 14 Solutions, 21
3.5 Total Probability Rule, 14 References, 26
CHAPTER 4 Discrete Probability Distributions 28
Review Of Key Concepts, 28 4.4 Methods For Using The Binomial Distribution, 30
4.1 Random Variable, 28 4.5 Using Electronic Tables, 30
4.2 Combinations, Permutations, And Factorial, 4.6 Expected Value Of The Binomial Distribution, 31
28 4.7 Variance Of The Binomial Distribution, 31
4.3 Binomial Probability Distribution, 29
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4.8 Poisson Distribution, 32 4.11 Poisson Approximation To The
4.9 Use Of Electronic Tables For BinomialDistribution, 33
PoissonProbabilities, 32 Problems, 33
4.10 Expected Value And Variance Of The Solutions, 38
PoissonDistribution, 33 References, 43
CHAPTER 5 Continuous Probability Distributions 44
Review Of Key Concepts, 44 5.7 Inverse Normal Distribution, 47
5.1 Probability Density Function, 44 5.8 Use Of Electronic Tables For The
5.2 Expected Value And Variance Of A NormalDistribution, 47
ContinuousRandom Variable, 45 5.9 Normal Approximation To The
5.3 Normal Probability Density Function, 45 BinomialDistribution, 48
5.4 Empirical And Symmetry Properties Of 5.10 Normal Approximation To The
TheNormal Distribution, 45 PoissonDistribution, 50
5.5 Calculation Of Probabilities For A Problems, 50
StandardNormal Distribution, 46 Solutions, 54
5.6 Calculation Of Probabilities For A General References, 65
NormalDistribution, 47
CHAPTER 6 Estimation 66
Review Of Key Concepts, 66 6.8.2 Factors Influencing The Length Of
6.1 Relationship Of Population To Sample, 66 AConfidence Interval, 69
6.2 Random-Number Tables, 66 6.9 Estimation Of The Variance Of A Distribution, 69
6.3 Randomized Clinical Trials, 67 6.10 Estimation For The Binomial Distribution, 70
6.3.1 Techniques Of Study Design In 6.10.1 Large-Sample Method, 70
Randomized Clinical Trials, 67 6.10.2 Small-Sample Method, 71
6.4 Sampling Distribution, 67 6.11 Estimation For The Poisson Distribution, 71
6.5 Estimation Of The Mean Of A Distribution, 6.12 One-Sided Confidence Limits, 72
67 Problems, 73
6.6 Standard Error Of The Mean, 68 Solutions, 76
6.7 The Central-Limit Theorem, 68 Reference, 79
6.8 Interval Estimation For The Mean, 68
6.8.1 Use Of Confidence Intervals
ForDecision-Making Purposes,
69
CHAPTER 7 Hypothesis Testing: One-Sample Inference 80
Review Of Key Concepts, 80 7.7.1 Relative Advantages Of
7.1 Fundamentals Of Hypothesis Testing, 80 Hypothesis- Testing Versus
7.2 One-Sample T Test, 80 Confidence-Interval Approaches, 85
7.3 Guidelines For Assessing 7.8 One-Sample 2 Test, 85
StatisticalSignificance, 81 7.9 One-Sample Inference For The
7.4 Two-Sided Alternatives, 82 BinomialDistribution, 86
7.5 The Power Of A Test, 83 7.10 One-Sample Inference For The
7.6 Sample Size, 84 PoissonDistribution, 87
7.7 Relationship Between Hypothesis Testing Problems, 88
AndConfidence Intervals, 85 Solutions, 92
References, 98
, STUDY GUIDE/FUNDAMENTALS OF BIOSTATISTICS v
CHAPTER 8 Hypothesis Testing: Two-Sample Inference 99
Review Of Key Concepts, 99 8.4 T Test For Independent Samples—
8.1 Paired T Test, 99 UnequalVariances, 102
8.2 Two-Sample T Test For Independent 8.5 Sample-Size Determination For Comparing
Samples—Equal Variances, 100 TwoMeans From Independent Samples, 104
8.3 F Test For The Equality Of Two Variances, Problems, 105
101 Solutions, 111
8.3.1 Characteristics Of The F References, 122
Distribution, 102
CHAPTER 9 Nonparametric Methods 123
Review Of Key Concepts, 123 9.3 The Wilcoxon Signed-Rank Test, 124
9.1 Types Of Data, 123 9.4 The Wilcoxon Rank-Sum Test, 126
9.2 The Sign Test, 123 Problems, 127
9.2.1 Large-Sample Test, 123 Solutions, 128
9.2.2 Small-Sample Test, 124 Reference, 131
CHAPTER 10 Hypothesis Testing: Categorical Data 132
Review Of Key Concepts, 132 10.3.1 Computation Of P-Values With
10.1 Comparison Of Two Binomial Proportions, Fisher’sExact Test, 136
132 10.4 Mcnemar’s Test For Correlated Proportions, 136
10.1.1 Two-Sample Test For 10.5 Sample Size For Comparing Two
BinomialProportions (Normal- BinomialProportions, 138
Theory Version), 132 10.6 R C Contingency Tables, 139
10.2 The 2 2 Contingency-Table Approach, 133 10.7 Chi-Square Goodness-Of-Fit Test, 141
10.2.1 Relationship Between The Chi- 10.8 The Kappa Statistic, 143
SquareTest And The Two-Sample Problems, 144
Test For Binomial Proportions, 135 Solutions, 148
10.3 Fisher’s Exact Test, 135 References, 158
CHAPTER 11 Regression And Correlation Methods 159
Review Of Key Concepts, 159 11.8.1 One-Sample Inference, 166
11.1 The Linear-Regression Model, 159 11.8.2 Two-Sample Inference, 167
11.2 Fitting Regression Lines—The Method Of 11.8.3 Sample Size Estimation For
LeastSquares, 160 CorrelationCoefficients, 168
11.3 Testing For The Statistical Significance 11.9 Multiple Regression, 168
Of ARegression Line, 161 11.9.1 Multiple Regression Model, 168
11.3.1 Short Computational Form For The F 11.9.2 Interpretation Of
Test, 162 RegressionCoefficients,
11.4 The T Test Approach To Significance Testing 169
ForLinear Regression, 163 11.9.3 Hypothesis Testing, 169
11.5 Interval Estimation For Linear Regression, 164 11.9.4 Several Types Of Correlation
11.6 R2, 165 AssociatedWith Multiple Regression,
11.7 Assessing The Goodness Of Fit Of 170
Regression Lines, 165 11.10 Rank Correlation, 170
11.8 The Correlation Coefficient, 166 Problems, 171
Solutions, 176
References, 185
Author:Rosner All Chapters
,CONTENTS
Preface, Vii
CHAPTER 1 General Overview 1
There Are No Problems/Solutions In Chapter 1 Of The Textbook.
CHAPTER 2 Descriptive Statistics 2
Review Of Key Concepts, 2 2.2.2 Quasi-Range, 6
2.1 Measures Of Location, 2 2.2.3 Standard Deviation, Variance, 7
2.1.1 Arithmetic Mean, 2 2.2.4 Coefficient Of Variation (CV), 8
2.1.2 Median, 3 2.3 Some Other Methods For Describing Data, 8
2.1.3 Stem-And-Leaf Plots, 2.3.1 Frequency Distribution, 8
3 2.3.2 Box Plot, 8
2.1.4 Percentiles, 4 Problems, 9
2.1.5 Geometric Mean, 5 Solutions, 10
2.2 Measures Of Spread, 6 Reference, 11
2.2.1 Range, 6
CHAPTER 3 Probability 12
Review Of Key Concepts, 12 3.6 Sensitivity, Specificity, Predictive Values
3.1 Frequency Definition Of Probability, 12 OfScreening Tests, 15
3.2 Multiplication Law Of Probability, 13 3.6.1 ROC Curves, 16
3.3 Addition Law Of Probability, 13 3.7 Bayes’ Theorem, 17
3.4 Conditional Probability, 13 Problems, 18
3.4.1 Relative Risk, 14 Solutions, 21
3.5 Total Probability Rule, 14 References, 26
CHAPTER 4 Discrete Probability Distributions 28
Review Of Key Concepts, 28 4.4 Methods For Using The Binomial Distribution, 30
4.1 Random Variable, 28 4.5 Using Electronic Tables, 30
4.2 Combinations, Permutations, And Factorial, 4.6 Expected Value Of The Binomial Distribution, 31
28 4.7 Variance Of The Binomial Distribution, 31
4.3 Binomial Probability Distribution, 29
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4.8 Poisson Distribution, 32 4.11 Poisson Approximation To The
4.9 Use Of Electronic Tables For BinomialDistribution, 33
PoissonProbabilities, 32 Problems, 33
4.10 Expected Value And Variance Of The Solutions, 38
PoissonDistribution, 33 References, 43
CHAPTER 5 Continuous Probability Distributions 44
Review Of Key Concepts, 44 5.7 Inverse Normal Distribution, 47
5.1 Probability Density Function, 44 5.8 Use Of Electronic Tables For The
5.2 Expected Value And Variance Of A NormalDistribution, 47
ContinuousRandom Variable, 45 5.9 Normal Approximation To The
5.3 Normal Probability Density Function, 45 BinomialDistribution, 48
5.4 Empirical And Symmetry Properties Of 5.10 Normal Approximation To The
TheNormal Distribution, 45 PoissonDistribution, 50
5.5 Calculation Of Probabilities For A Problems, 50
StandardNormal Distribution, 46 Solutions, 54
5.6 Calculation Of Probabilities For A General References, 65
NormalDistribution, 47
CHAPTER 6 Estimation 66
Review Of Key Concepts, 66 6.8.2 Factors Influencing The Length Of
6.1 Relationship Of Population To Sample, 66 AConfidence Interval, 69
6.2 Random-Number Tables, 66 6.9 Estimation Of The Variance Of A Distribution, 69
6.3 Randomized Clinical Trials, 67 6.10 Estimation For The Binomial Distribution, 70
6.3.1 Techniques Of Study Design In 6.10.1 Large-Sample Method, 70
Randomized Clinical Trials, 67 6.10.2 Small-Sample Method, 71
6.4 Sampling Distribution, 67 6.11 Estimation For The Poisson Distribution, 71
6.5 Estimation Of The Mean Of A Distribution, 6.12 One-Sided Confidence Limits, 72
67 Problems, 73
6.6 Standard Error Of The Mean, 68 Solutions, 76
6.7 The Central-Limit Theorem, 68 Reference, 79
6.8 Interval Estimation For The Mean, 68
6.8.1 Use Of Confidence Intervals
ForDecision-Making Purposes,
69
CHAPTER 7 Hypothesis Testing: One-Sample Inference 80
Review Of Key Concepts, 80 7.7.1 Relative Advantages Of
7.1 Fundamentals Of Hypothesis Testing, 80 Hypothesis- Testing Versus
7.2 One-Sample T Test, 80 Confidence-Interval Approaches, 85
7.3 Guidelines For Assessing 7.8 One-Sample 2 Test, 85
StatisticalSignificance, 81 7.9 One-Sample Inference For The
7.4 Two-Sided Alternatives, 82 BinomialDistribution, 86
7.5 The Power Of A Test, 83 7.10 One-Sample Inference For The
7.6 Sample Size, 84 PoissonDistribution, 87
7.7 Relationship Between Hypothesis Testing Problems, 88
AndConfidence Intervals, 85 Solutions, 92
References, 98
, STUDY GUIDE/FUNDAMENTALS OF BIOSTATISTICS v
CHAPTER 8 Hypothesis Testing: Two-Sample Inference 99
Review Of Key Concepts, 99 8.4 T Test For Independent Samples—
8.1 Paired T Test, 99 UnequalVariances, 102
8.2 Two-Sample T Test For Independent 8.5 Sample-Size Determination For Comparing
Samples—Equal Variances, 100 TwoMeans From Independent Samples, 104
8.3 F Test For The Equality Of Two Variances, Problems, 105
101 Solutions, 111
8.3.1 Characteristics Of The F References, 122
Distribution, 102
CHAPTER 9 Nonparametric Methods 123
Review Of Key Concepts, 123 9.3 The Wilcoxon Signed-Rank Test, 124
9.1 Types Of Data, 123 9.4 The Wilcoxon Rank-Sum Test, 126
9.2 The Sign Test, 123 Problems, 127
9.2.1 Large-Sample Test, 123 Solutions, 128
9.2.2 Small-Sample Test, 124 Reference, 131
CHAPTER 10 Hypothesis Testing: Categorical Data 132
Review Of Key Concepts, 132 10.3.1 Computation Of P-Values With
10.1 Comparison Of Two Binomial Proportions, Fisher’sExact Test, 136
132 10.4 Mcnemar’s Test For Correlated Proportions, 136
10.1.1 Two-Sample Test For 10.5 Sample Size For Comparing Two
BinomialProportions (Normal- BinomialProportions, 138
Theory Version), 132 10.6 R C Contingency Tables, 139
10.2 The 2 2 Contingency-Table Approach, 133 10.7 Chi-Square Goodness-Of-Fit Test, 141
10.2.1 Relationship Between The Chi- 10.8 The Kappa Statistic, 143
SquareTest And The Two-Sample Problems, 144
Test For Binomial Proportions, 135 Solutions, 148
10.3 Fisher’s Exact Test, 135 References, 158
CHAPTER 11 Regression And Correlation Methods 159
Review Of Key Concepts, 159 11.8.1 One-Sample Inference, 166
11.1 The Linear-Regression Model, 159 11.8.2 Two-Sample Inference, 167
11.2 Fitting Regression Lines—The Method Of 11.8.3 Sample Size Estimation For
LeastSquares, 160 CorrelationCoefficients, 168
11.3 Testing For The Statistical Significance 11.9 Multiple Regression, 168
Of ARegression Line, 161 11.9.1 Multiple Regression Model, 168
11.3.1 Short Computational Form For The F 11.9.2 Interpretation Of
Test, 162 RegressionCoefficients,
11.4 The T Test Approach To Significance Testing 169
ForLinear Regression, 163 11.9.3 Hypothesis Testing, 169
11.5 Interval Estimation For Linear Regression, 164 11.9.4 Several Types Of Correlation
11.6 R2, 165 AssociatedWith Multiple Regression,
11.7 Assessing The Goodness Of Fit Of 170
Regression Lines, 165 11.10 Rank Correlation, 170
11.8 The Correlation Coefficient, 166 Problems, 171
Solutions, 176
References, 185
