Pitfalls of Data Analysis. - Practical Assessment, Research & Evaluation

It can be surprising to naive observers that statistics from different research studies concerning the same issue can produce very dissimilar or contradictory results. In order to resolve this paradox, many people conclude that statistics are not actually reliable indicators of reality. Those versed in statistics, however, understand that statistics rely on assumptions. Proceeding from different assumptions, or claiming assumptions which don't apply to the research situation in question can lead to divergent results. This article attempts to warn against the frequent misuses and abuses of statistics. Although these issues are familiar to most statisticians, they can be easily overlooked. These problems can be considered in three broad classes of statistical pitfalls: sources of bias, errors in methodology, and misinterpretation of results.