An Introduction to Statistical Modelling

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.

W. J. Krzanowski is the author of An Introduction to Statistical Modelling, published by Wiley.

Series preface
Preface
Introduction
Models in data analysis
Populations and samples
Variables and factors
Observational and experimental data
Statistical models
Distributions and inference
Random variables and probability distributions
Probability distributions as models
Some common distributions
Sampling distributions
Inference
Postscript
Normal response and quantitative explanatory variables: regression
Motivation
Simple regression
Multiple regression
Model building
Model validation and criticism
Comparison of regressions
Non-linear models
Normal response and qualitative explanatory variables: analysis of variance
Motivation
One-way arrangements
Cross-classifications
Nested classifications
A general approach via multiple regression
Analysis of covariance
Non-normality: the theory of generalized linear models
Introduction
The generalized linear model
Fitting the model
Assessing the fit of a model: deviance
Comparing models: analysis of deviance
Normal models
Inspecting and checking models
Software
Binomial response variables: logistic regression and related method
Binary response data
Modelling binary response probabilities
Logistic regression
Related methods
Ordered polytomous data
Tables of counts and log-linear models
Introduction
Data mechanisms and distributions
Log-linear models for means
Models for contingency tables
Analysis
Applications
Further topics
Introduction
Continuous non-normal responses
Quasi-likelihood
Overdispersion
Non-parametric models
Conclusion: the art of model building
References
Index
Table of Contents provided by Publisher. All Rights Reserved.

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An Introduction to Statistical Modelling

Summary

Author Biography

Table of Contents

Supplemental Materials