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

Preface.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.