ABSTRACT
Quintessentially, statistics is about solving problems: Data (measurements or observations) relevant to these problems are collected, and statistical analyses are used to provide useful answers. But the path from data collection to analysis and interpretation is often not straightforward. Most reallife applications of statistical methodology have one or more nonstandard features, meaning in practice that there are few routine statistical questions, although there are questionable statistical routines. Many statistical pitfalls lie in wait for the unwary. Indeed, statistics is perhaps more open to misuse than most other subjects, particularly by the nonstatistician with access to powerful statistical software. The misleading average, the graph with ‘fiddled axes’, the inappropriate p-value, and the linear regression fitted to nonlinear data are just four examples of horror stories that are part of statistical folklore.
