 a misuse of statistics occurs when a statistical argument asserts a falsehood. in some cases, the misuse may be accidental. in others, it is purposeful and for the gain of the perpetrator. when the statistical reason involved is false or misapplied, this constitutes a statistical fallacy. the false statistics trap can be quite damaging to the quest for knowledge. for example, in medical science, correcting a falsehood may take decades and cost lives. misuses can be easy to fall into. professional scientists, even mathematicians and professional statisticians, can be fooled by even some simple methods, even if they are careful to check everything. scientists have been known to fool themselves with statistics due to lack of knowledge of probability theory and lack of standardization of their tests. ==importance== statistics may be a principled means of debate with opportunities for agreement, porter considered the history of cost-benefit analysis. while this is perhaps more economical than statistical, it is a quantitative decision-making technique considered to be in the statistical domain. but this is true only if the parties agree to a set of rules. misuses of statistics violate the rules. ==definition, limitations and context== one usable definition is: "misuse of statistics: using numbers in such a manner that - either by intent, or through ignorance or carelessness - the conclusions are unjustified or incorrect." the "numbers" include misleading graphics discussed elsewhere. the term is not commonly encountered in statistics texts and no authoritative definition is known. it is a generalization of lying with statistics which was richly described by examples from statisticians 60 years ago. the definition confronts some problems (some are addressed by the source): #statistics usually produces probabilities; conclusions are provisional #the provisional conclu
Ethics_and_statistics Laymen_and_statistics Misuse_of_statistics