Statistics - Crawley, Michael J.

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Auteur(s) : Crawley, Michael J.

Editeur : John Wiley & Sons

Langue : Anglais

Parution : 01/11/2014

Format : Moyen, de 350g à 1kg

Nombre de pages : 368

Expédition : 611

Dimensions : 24.4 x 17.0 x 1.9

ISBN : 9781118941096

Résumé :

...I know of no better book of its kind... (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)

A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R

This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a?wide range of disciplines. Step-by-step instructions?help the non-statistician to fully understand the methodology.? The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.

Includes numerous worked examples and exercises within each chapter.

...

Biographie:

Preface xi

Chapter 1 Fundamentals 1

Everything Varies 2

Significance 3

Good and Bad Hypotheses 3

Null Hypotheses 3

p Values 3

Interpretation 4

Model Choice 4

Statistical Modelling 5

Maximum Likelihood 6

Experimental Design 7

The Principle of Parsimony (Occam's Razor) 8

Observation, Theory and Experiment 8

Controls 8

Replication: It's the ns that Justify the Means 8

How Many Replicates? 9

Power 9

Randomization 10

Strong Inference 14

Weak Inference 14

How Long to Go On? 14

Pseudoreplication 15

Initial Conditions 16

Orthogonal Designs and Non-Orthogonal Observational Data 16

Aliasing 16

Multiple Comparisons 17

Summary of Statistical Models in R 18

Organizing Your Work 19

Housekeeping within R 20

References 22

Further Reading 22

Chapter 2 Dataframes 23

Selecting Parts of a Dataframe: Subscripts 26

Sorting 27

Summarizing the Content of Dataframes 29

Summarizing by Explanatory Variables 30

First Things First: Get to Know Your Data 31

Relationships 34

Looking for Interactions between Continuous Variables 36

Graphics to Help with Multiple Regression 39

Interactions Involving Categorical Variables 39

Further Reading 41

Chapter 3 Central Tendency 42

Further Reading 49

Chapter 4 Variance 50

Degrees of Freedom 53

Variance 53

Variance: A Worked Example 55

Variance and Sample Size 58

Using Variance 59

A Measure of Unreliability 60

Confidence Intervals 61

Bootstrap 62

Non-constant Variance: Heteroscedasticity 65

Further Reading 65

Chapter 5 Single Samples 66

Data Summary in the One-Sample Case 66

The Normal Distribution 70

Calculations Using z of the Normal Distribution 76

Plots for Testing Normality of Single Samples 79

Inference in the One-Sample Case 81

Bootstrap in Hypothesis Testing with Single Samples 81

Student's t Distribution 82

Higher-Order Moments of a Distribution 83

Skew 84

Kurtosis 86

Reference 87

Further Reading 87

Chapter 6 Two Samples 88

Comparing Two Variances 88

Comparing Two Means 90

Student's t Test 91

Wilcoxon Rank-Sum Test 95

Tests on Paired Samples 97

The Binomial Test 98

Binomial Tests to Compare Two Proportions 100

Chi-Squared Contingency Tables 100

Fisher's Exact Test 105

Correlation and Covariance 108

Correlation and the Variance of Differences between Variables 110

Scale-Dependent Correlations 112

Reference 113

Further Reading 113

Chapter 7 Regression 114

Linear Regression 116

Linear Regression in R 117

Calculations Involved in Linear Regression 122

Partitioning Sums of Squares in Regression: SSY = SSR + SSE 125

Measuring the Degree of Fit, r 2 133

Model Checking 134

Transformation 135

Polynomial Regression 140

Non-Linear Regression 142

Generalized Additive Models 146

Influence 148

Further Reading 149

Chapter 8 Analysis of Variance 150

One-Way ANOVA 150

Shortcut Formulas 157

Effect Sizes 159

Plots for Interpreting One-Way ANOVA 162

Factorial Experiments 168

Pseudoreplication: Nested Designs and Split Plots 173

Split-Plot Experiments 174

Random Effects and Nested Designs 176

Fixed or Random Effects? 177

Removing the Pseudorep...

Sommaire:

Michael J. Crawley, FRS, Department of Biological Sciences, Imperial College of Science, Technology and Medicine. Author of three bestselling Wiley statistics titles and five life science books....