Editing 2440: Epistemic Uncertainty

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==Explanation==
 
==Explanation==
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This comic is a comparison of two different research studies. One of these studies shows "regular uncertainty". One of these studies shows "epistemic uncertainty." In both panels, the core data is the same. The drug in question is 74% effective. However, the uncertainty qualities are different. The first is straightforward. The confidence interval (the error bars on the chart) is from 63 to 81%. The second panel includes the additional wrinkle of "George the Data Tamperer, whose whims are unpredictable."
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In statistics, a {{w|confidence interval}} is an estimate which provides a range of values. These values are based on the statistical probability that the data collected represents a certain result. The confidence interval is a reflection on the uncertainty imposed by the limits of study sample sizes. No study will ever have an infinite data set.{{Citation needed}} As a result, it is possible for different studies to give slightly different results.  Averaging the results of multiple studies can give a result that is probably more accurate. The result given may still be skewed. A small skew is more probable than a large one, though. For example, if a drug was 80% effective it would be possible for several small studies to show a spread of different results with an average of 74% effectiveness. If the drug was 99% effective it would still be possible to randomly end up with the same data. However, this would be highly unlikely. This gives us a spread of "likely" predictions. Predictions outside a certain interval are considered too unlikely to be realistic.
 
In statistics, a {{w|confidence interval}} is an estimate which provides a range of values. These values are based on the statistical probability that the data collected represents a certain result. The confidence interval is a reflection on the uncertainty imposed by the limits of study sample sizes. No study will ever have an infinite data set.{{Citation needed}} As a result, it is possible for different studies to give slightly different results.  Averaging the results of multiple studies can give a result that is probably more accurate. The result given may still be skewed. A small skew is more probable than a large one, though. For example, if a drug was 80% effective it would be possible for several small studies to show a spread of different results with an average of 74% effectiveness. If the drug was 99% effective it would still be possible to randomly end up with the same data. However, this would be highly unlikely. This gives us a spread of "likely" predictions. Predictions outside a certain interval are considered too unlikely to be realistic.
  

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