Publisher's Synopsis
The main objective of is book is working with probability distributions, hypothesis testing and analysis of variance models. The most important contents are: Using Probability Distributions Parametric Distributions Nonparametric Distributions Modeling Data Using the Distribution Fitting Tool Visually Exploring Random Number Generation Probability Density Functions Cumulative Distribution Functions Inverse Cumulative Distribution Functions Distribution Statistics Functions Distribution Fitting Functions Random Number Generators Probability Distributions Used for Multivariate Modeling Gaussian Mixture Models Copulas: Generate Correlated Samples Random Number Generation Representing Sampling Distributions Using Markov Chain Samplers Using Slice Sampling Generating Data Using the Pearson System Generating Data Using the Johnson System Hypothesis Tests Analysis of Variance One-Way ANOVA Two-Way ANOVA N-Way ANOVA Other ANOVA Models Analysis of Covariance Nonparametric Methods MANOVA ANOVA with Multiple Responses
