INDICE: Preface Part I Data in statistics and R 1 Basic R 1.1 Preliminaries1.2 Modes 1.3 Vectors 1.4 Arithmetic operators and special values 1.5 Objects1.6 Programming 1.7 Packages 1.8 Graphics 1.9 Customizing the workspace 1.10 Projects 1.12 Assignments 2 Data in statistics and in R 2.1 Types of data 2.2 Objects that hold data 2.3 Data organization 2.4 Data import, export and connections 2.5 Data manipulation 2.6 Manipulating strings 2.7 Assignments 3 Presenting data 3.1 Tables and the flavors of apply( 3.2 Bar plots 3.3 Histograms 3.4 Dot charts 3.5 Scatter plots 3.6 Lattice plots 3.7 Three-dimensional plots and contours 3.8 Assignments Part II Probability, densities and distributions 4Probability and random variables 4.1 Set theory 4.2 Trials, events and experiments 4.3 Definitions and properties of probability 4.4 Conditional probability and independence 4.5 Algebra with probabilities 4.6 Random variables 4.7 Assignments 5 Discrete densities and distributions 5.1 Densities 5.2 Distribution5.3 Properties 5.4 Expected values 5.5 Variance and standard deviation 5.6 The binomial 5.7 The Poisson 5.8 Estimating parameters 5.9 Some useful discrete densities 5.10 Assignments 6 Continuous distributions and densities 6.1 Distributions 6.2 Densities 6.3 Properties 6.4 Expected values 6.5 Variance and standard deviation 6.6 Areas under density curves 6.7 Inverse distributions and simulations 6.8 Some useful continuous densities 6.9 Assignments 7 The normal and sampling densities 7.1 The normal density 7.2 Applications of the normal 7.3Data transformations 7.4 Random samples and sampling densities 7.5 A detour: using R efficiently 7.6 The sampling density of the mean 7.7 The sampling density of proportion 7.8 The sampling density of intensity 7.9 The sampling density of variance 7.10 Bootstrap: arbitrary parameters of arbitrary densities 7.11 Assignments Part III Statistics 8 Exploratory data analysis 8.1 Graphical methods 8.2 Numerical summaries 8.3 Visual summaries 8.4 Assignments 9 Point andinterval estimation 9.1 Point estimation 9.1.1 Maximum likelihood estimators 9.2 Interval estimation 9.3 Point and interval estimation for arbitrary densities 9.4 Assignments 10 Single sample hypotheses testing 10.1 Null and alternative hypotheses 10.2 Large sample hypothesis testing 10.3 Small sample hypotheses testing 10.4 Arbitrary parameters of arbitrary densities 10.5 p-values 10.6Assignments 11 Power and sample size for single samples 11.1 Large sample 11.2 Small samples 11.3 Power and sample size for arbitrary densities 11.4 Assignments 12 Two samples 12.1 Large samples 12.2 Small samples 12.3 Unknown densities 12.4 Assignments 13 Power and sample size for two samples 13.1 Two means from normal populations 13.2 Two proportions 13.3 Two rates 13.4 Assignments 14Simple linear regression 14.1 Simple linear models 14.2 Estimating regressioncoefficients 14.3 The model goodness of fit 14.4 Hypothesis testing and confidence intervals 14.5 Model assumptions 14.6 Model diagnostics 14.7 Power and sample size for the correlation coefficient 14.8 Assignments 15 Analysis of variance 15.1 One-way, fixed-effects ANOVA 15.2 Non-parametric one-way ANOVA 15.3One-way, random-effects ANOVA 15.4 Two-way ANOVA 15.5 Two-way linear mixed effects models 15.6 Assignments 16 Simple logistic regression 16.1 Simple binomial logistic regression 16.2 Fitting and selecting models 16.3 Assessing goodness of fit 16.4 Diagnostics 16.5 Assignments 17 Application: the shape of wars to come 17.1 A statistical profile of the war in Iraq 17.2 A statistical profile of the second Intifada References R Index General Index
- ISBN: 978-0-470-75805-2
- Editorial: John Wiley & Sons
- Encuadernacion: Cartoné
- Páginas: 632
- Fecha Publicación: 17/10/2008
- Nº Volúmenes: 1
- Idioma: Inglés