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An Introduction to Statistical M... par Krzanowski, Wojtek J livre de poche / softback-
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Numéro de l'objet eBay :304950411650
Dernière mise à jour le 04 oct. 2024 05:34:31 Paris. Afficher toutes les modificationsAfficher toutes les modifications
Caractéristiques de l'objet
- État
- ISBN
- 0470711019
- EAN
- 9780470711019
- Release Title
- An Introduction to Statistical Modelling
- Artist
- Krzanowski, Wojtek J.
- Brand
- N/A
- Colour
- N/A
- Book Title
- An Introduction to Statistical Modelling
- Subject Area
- Mathematics
- Publication Name
- Introduction to Statistical Modelling
- Publisher
- Wiley & Sons, Incorporated, John
- Item Length
- 9.3 in
- Subject
- Probability & Statistics / General
- Publication Year
- 2010
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 0.6 in
- Item Weight
- 14 Oz
- Item Width
- 6.4 in
- Number of Pages
- 272 Pages
À propos de ce produit
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0470711019
ISBN-13
9780470711019
eBay Product ID (ePID)
92379272
Product Key Features
Number of Pages
272 Pages
Language
English
Publication Name
Introduction to Statistical Modelling
Publication Year
2010
Subject
Probability & Statistics / General
Type
Textbook
Subject Area
Mathematics
Format
Trade Paperback
Dimensions
Item Height
0.6 in
Item Weight
14 Oz
Item Length
9.3 in
Item Width
6.4 in
Additional Product Features
Intended Audience
Scholarly & Professional
Dewey Edition
21
TitleLeading
An
Dewey Decimal
519.5
Table Of Content
Series preface. Preface. 1. Introduction. 1.1 Models in data analysis. 1.2 Populations and samples. 1.3 Variables and factors. 1.4 Observational and experimental data. 1.5 Statistical models. 2. Distributions and inference. 2.1 Random variables and probability distributions. 2.2 Probability distributions as models. 2.3 Some common distributions. 2.4 Sampling distributions. 2.5 Inference. 2.6 Postscript. 3. Normal response and quantitative explanatory variables: regression. 3.1 Motivation. 3.2 Simple regression. 3.3 Multiple regression. 3.4 Model building. 3.5 Model validation and criticism. 3.6 Comparison of regressions. 3.7 Non-linear models. 4. Normal response and qualitative explanatory variables: analysis of variance. 4.1 Motivation. 4.2 One-way arrangements. 4.3 Cross-classifications. 4.4 Nested classifications. 4.5 A general approach via multiple regression. 4.6 Analysis of covariance. 5. Non-normality: the theory of generalized linear models. 5.1 Introduction. 5.2 The generalized linear model. 5.3 Fitting the model. 5.4 Assessing the fit of a model: deviance. 5.5 Comparing models: analysis of deviance. 5.6 Normal models. 5.7 Inspecting and checking models. 5.8 Software. 6. Binomial response variables: logistic regression and related method. 6.1 Binary response data. 6.2 Modelling binary response probabilities. 6.3 Logistic regression. 6.4 Related methods. 6.5 Ordered polytomous data. 7. Tables of counts and log-linear models. 7.1 Introduction. 7.2 Data mechanisms and distributions. 7.3 Log-linear models for means. 7.4 Models for contingency tables. 7.5 Analysis. 7.6 Applications. 8. Further topics. 8.1 Introduction. 8.2 Continuous non-normal responses. 8.3 Quasi-likelihood. 8.4 Overdispersion. 8.5 Non-parametric models. 8.6 Conclusion: the art of model building. References. Index.
Synopsis
Statisticians rely heavily on making models of 'causal situations' in order to fully explain and predict events. Modelling therefore plays a vital part in all applications of statistics and is a component of most undergraduate programmes., Statisticians rely heavily on making models of 'causal situations' in order to fully explain and predict events. Modelling therefore plays a vital part in all applications of statistics and is a component of most undergraduate programmes. 'An Introduction to Statistical Modelling' provides a single reference with an applied slant that caters for all three years of a degree course. The book concentrates on core issues and only the most essential mathematical justifications are given in detail. Attention is firmly focused on the statistical aspects of the techniques, in this lively, practical approach.
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