If a study “Computer games – art or not?” was conducted on participants between the ages of fifty and sixty then it’s results will probably be quite different from the results of the same study conducted on participants between the ages of fifteen and twenty. The weak place here is the fact that the scientists may not put an important factor as relevant in the study. When conducting an experiment, scientists have to conduct lists of relevant factors – for a political poll for example it can be the age, income or religious beliefs of the participants. Part one: Kinds of Data Manipulation and Reasons behind ThemĪn issue that is part of an even bigger issue that is: scientists are looking for results (Because that means research grants etc.) and thus they sometimes deliberately or unintentionally manipulate data to fit their hypothesis.
Most importantly – what red flags to look for when reading an article or a project that might be a sign of data manipulation. This chapter will try to describe the kinds of data manipulations that there are and the ways to deal with them. Misuse of statistics does include data forgery – the process in which data is created without any connection to the object of the data but the most important kinds of misuse of statistics are these that involve real data that is presented in a manner that may be misleading and even dangerous. It is these examples that we will concentrate on in this chapter. Arguably the most common kind of data manipulation is misuse of statistics – many click-bait article titles on the internet are based on misuse of statistic as are some political and economic arguments. In the modern world we encounter data manipulation every day. An experiment based on data that has been manipulated is risky and unpredictable.
Data manipulation may result in distorted perception of a subject which may lead to false theories being build and tested. Data manipulation is the process in which scientific data is forged, presented in an unprofessional way or changed with disregard to the rules of the academic world.