This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book describes graphical procedures for evaluating goodness-of-fit, and presents tests based on the empirical distribution function. These are informal procedures based mainly on the probability plot, useful for exploring data and for supplementing the formal testing procedures of the other chapters. It deals with tests based on regression and correlation, and reviews transformation techniques and chi-square-type tests. The book collects these together, fills in some omissions, and gives examples; there is also a discussion on probability plotting of censored data. The classical chi-square goodness-of-fit tests are reviewed first and then recent developments involving general quadratic forms and nonstandard chi-squared statistics are also discussed. The book focuses on the analysis and detection of outliers. It devotes to the presentation, and discusses of goodness-of-fit techniques.