Produktbild: Engineering Biostatistics

Engineering Biostatistics An Introduction Using MATLAB and Winbugs

139,99 €

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

06.11.2017

Verlag

John Wiley & Sons

Seitenzahl

992

Maße (L/B/H)

26,1/18,1/4,3 cm

Gewicht

1642 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-16896-6

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

06.11.2017

Verlag

John Wiley & Sons

Seitenzahl

992

Maße (L/B/H)

26,1/18,1/4,3 cm

Gewicht

1642 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-16896-6

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Engineering Biostatistics
  • Preface v
     
    1 Introduction 1
     
    Chapter References 7
     
    2 The Sample and Its Properties 9
     
    2.1 Introduction 9
     
    2.2 A MATLAB Session on Univariate Descriptive Statistics 10
     
    2.3 Location Measures 12
     
    2.4 Variability Measures 15
     
    2.4.1 Ranks 24
     
    2.5 Displaying Data 25
     
    2.6 Multidimensional Samples: Fisher's Iris Data and Body Fat Data 29
     
    2.7 Multivariate Samples and Their Summaries 35
     
    2.8 Principal Components of Data 40
     
    2.9 Visualizing Multivariate Data 45
     
    2.10 Observations as Time Series 49
     
    2.11 About Data Types 52
     
    2.12 Big Data Paradigm 53
     
    2.13 Exercises 55
     
    Chapter References 70
     
    3 Probability, Conditional Probability, and Bayes' Rule 73
     
    3.1 Introduction 73
     
    3.2 Events and Probability 74
     
    3.3 Odds 85
     
    3.4 Venn Diagrams 86
     
    3.5 Counting Principles 88
     
    3.6 Conditional Probability and Independence 92
     
    3.6.1 Pairwise and Global Independence 97
     
    3.7 Total Probability 97
     
    3.8 Reassesing Probabilities: Bayes' Rule 100
     
    3.9 Bayesian Networks 105
     
    3.10 Exercises 111
     
    Chapter References 130
     
    4 Sensitivity, Specificity, and Relatives 133
     
    4.1 Introduction 133
     
    4.2 Notation 134
     
    4.2.1 Conditional Probability Notation 138
     
    4.3 Combining Two or More Tests 141
     
    4.4 ROC Curves 144
     
    4.5 Exercises 149
     
    Chapter References 157
     
    5 Random Variables 159
     
    5.1 Introduction 159
     
    5.2 Discrete Random Variables 161
     
    5.2.1 Jointly Distributed Discrete Random Variables 166
     
    5.3 Some Standard Discrete Distributions 169
     
    5.3.1 Discrete Uniform Distribution 169
     
    5.3.2 Bernoulli and Binomial Distributions 170
     
    5.3.3 Hypergeometric Distribution 174
     
    5.3.4 Poisson Distribution 177
     
    5.3.5 Geometric Distribution 180
     
    5.3.6 Negative Binomial Distribution 183
     
    5.3.7 Multinomial Distribution 184
     
    5.3.8 Quantiles 186
     
    5.4 Continuous Random Variables 187
     
    5.4.1 Joint Distribution of Two Continuous Random Variables 192
     
    5.4.2 Conditional Expectation 193
     
    5.5 Some Standard Continuous Distributions 195
     
    5.5.1 Uniform Distribution 196
     
    5.5.2 Exponential Distribution 198
     
    5.5.3 Normal Distribution 200
     
    5.5.4 Gamma Distribution 201
     
    5.5.5 Inverse Gamma Distribution 203
     
    5.5.6 Beta Distribution 203
     
    5.5.7 Double Exponential Distribution 205
     
    5.5.8 Logistic Distribution 206
     
    5.5.9 Weibull Distribution 207
     
    5.5.10 Pareto Distribution 208
     
    5.5.11 Dirichlet Distribution 209
     
    5.6 Random Numbers and Probability Tables 210
     
    5.7 Transformations of Random Variables 211
     
    5.8 Mixtures 214
     
    5.9 Markov Chains 215
     
    5.10 Exercises 219
     
    Chapter References 232
     
    6 Normal Distribution 235
     
    6.1 Introduction 235
     
    6.2 Normal Distribution 236
     
    6.2.1 Sigma Rules 240
     
    6.2.2 Bivariate Normal Distribution 241
     
    6.3 Examples with a Normal Distribution 243
     
    6.4 Combining Normal Random Variables 246
     
    6.5 Central Limit Theorem 249
     
    6.6 Distributions Related to Normal 253
     
    6.6.1 Chi-square Distribution 254
     
    6.6.2 t-Distribution 258
     
    6.6.3 Cauchy Distribution 259
     
    6.6.4 F-Distribution 260
     
    6.6.5 Noncentral chi2, t, and F Distributions 262
     
    6.6.6 Lognormal Distribution 26