Applied Statistics in Biology - Diane K Michelson

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Résumé :

Preface xiii

1 Introduction 1

Statistics, 1

Application of Statistics, 1

Scientific Method, 2

Statistical Null Hypothesis, 4

Type I Error (?), 5

Type II Error (?), 5

Power of the Test, 6
P-Value Misuse, 8

Effect Size, 9

Diagnostic Tests, 10

Bias, 12

Summary, 13

SAS Code, 14

R Code, 19

JMP Method, 21

References, 25

Additional Reading, 25

2 Data Management 27

Data Management Plan, 27

Organize Files, 28

Data Workbooks, 29

Backup, 33

Securing Data, 33

Data Analysis, 33

Data Preservation, 34

Data Sharing, 35

Summary, 35

Additional Reading, 35

3 Distributions 37

Measures of Central Tendency, 37

Dispersion, 38

Accuracy and Precision, 41

Normal Distribution, 42

Normal Probability Plot, 43

Measures of Departures from Normality, 44

Tests of Normality, 45

Comparing Distributions, 48

Comparing Two Mean Estimates, 50

Student's t-Test, 50

Wald Z-Test, 54

Bootstrap, 54

Summary, 57

SAS Code, 58

R Code, 63

JMP Method, 68

References, 80

Additional Reading, 81

4 Goodness-of-fit 83

? 2 Distribution, 83

Enumeration Data, 83

Two Cell Tests, 85

Sample Size to Differentiate Alternative Ratios, 87

Contingency Tests, Goodness-of-Fit, 88

Contingency Tests, No Expected Distribution, 89

Meta-Analysis, 92

Summary, 94

SAS Code, 95

R Code, 100

JMP Method, 106

References, 121

Additional Reading, 121

5 Variance Analyses-gaussian 123

Factors, 123

Experimental Unit, 124

Effect Types, 124

One-Factor Analysis, 125

Experimental Error, 126

F-Distribution, 127

Replication, 128

Randomized Complete Block, 129

Arrangement, 130

Variance Analysis, 132

Block: Fixed or Random Effect?, 133

Mixed Model Analysis, 134

REML Estimation, 135

Significance of Effects, 136

Generalized Linear Mixed Model, 137

Conditional and Marginal Models, 138

Covariance Structure, 139

Negative Variance Estimates, 140

Means Comparisons, 142

Contrasts, 143

Estimate of a Difference, 144

BLUE and BLUP Estimates, 145

Multiplicity Adjustment, 146

Letter Codes, 147

Test CV, 148

Power Analyses, 148

Summary, 149

SAS Code, 149

R Code, 164

JMP Method, 173

References, 187

Additional Reading, 187

6 Correlation and Regression 189

Rank Correlations, 191

Linear Regression, 192

Model I, 194

Model II, 194

Prediction of Y from X, 196

Broad and Narrow Inference, 197

Regression Through the Origin, 198

Inverse Prediction, 198

Transformations for Linear Regression, 199

Nonlinear Regression, 203

Dosage Response, 206

Segmented or Spline Regression, 208

Logistic Regression, 209

Creating Plots for Publication, 213

Summary, 214

SAS Code, 214

R Code, 226

JMP Method, 236

References, 277

Additional Reading, 277

7 Regression in Anova 279

Unequally Spaced or Unequally Balanced Treatments, 281

Dummy Variables, 284

Optimum Treatment Level, 286

Comparison of Regression Response, 287

Comparison of Responses, 289

Non-Gaussian Data, 290

Summary, 291

SAS Code, 292

R Code, 300

JMP Method, 307

References, 324...

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