The apparent authenticity of published data can be as dangerous as it is inviting. This guide points out the main dangers (sampling errors measurement errors and invalid or unreliable procedures) and analyzes the various ways in which these problems arise -- giving numerous examples.Jacob discusses ways to solve these problems and when no solutions seem available he suggests appropriate disclaimers. An appendix critically evaluates several useful data sets.Designed especially to alert advanced undergraduates and fresh graduate students to the pitfalls that researchers commonly overlook this monograph also serves as a general reference volume on how to avoid those pitfalls.
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