Statistical Computing: An Introduction to Data Analysis using S-Plus

Statistical methods

Introduction to S-Plus

Experimental design

Central tendency

Probability

Variance

The Normal distribution

Power calculations

Understanding data: graphical analysis

Understanding data: tabular analysis

Classical tests

Bootstrap and jackknife

Statistical models in S-Plus

Regression

Analysis of variance

Analysis of covariance

Model criticism

Contrasts

Split-plot Anova

Nested designs and variance components analysis

Graphs, functions and transformations

Curve fitting and piecewise regression

Non-linear regression

Multiple regression

Model simplification

Probability distributions

Generalised linear models

Proportion data: binomial errors

Count data: Poisson errors

Binary response variables

Tree models

Non-parametric smoothing

Survival analysis

Time series analysis

Mixed effects models

Spatial statistics

Bibliography

Index