Statistics is the science that studies the collection, analysis, interpretation and presentation of data. It makes it possible to learn, to extract patterns from data as well as to measure, and communicate uncertainty. The application of statistical methods to scientific, industrial, or societal problems allows trends to be determined in a specific context while also predicting what may happen in the future.
It is therefore not surprising that in our fact-minded western cultures, the language of statistics is something very powerful to wield. When used correctly, statistical methods are very useful tools for analyzing what is happening in the world around us. On the other hand, statistics can easily be used to oversimplify a phenomenon or situation, thus ultimately resulting in confusing information, data misinterpretation, and deceived readers. Even worse, statistics can be purposely abused and misused in the attempt to sensationalize or inflate data reports and opinion polls related to social, economic, political, medical trends and conditions.
Nonsense is what results when the data analysis is conveyed with dishonesty, with the wrong wordings or with the application of an incorrect statistical approach. Nonsense is also what results when the data analysis is presented to an audience that does not know what the statistics mean.
Statistics plays an important role in the medical field and notably in the area of shared decision making. Many patients wish to know their individual risk of being diagnosed with a certain condition or what are their chances of survival when they undergo a certain treatments. Explaining data to patients is however not an easy task.
In this presentation, we review some use cases, which show how statistical data can easily be misinterpreted and, as such, should be avoided when using statistics for medical purposes.