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All the proposals so far are missing what people really want to know, which are two orthogonal metrics: How good/bad the crowd thinks the answer is. How heavily the crowd has weighed in. The first...
Answer
#1: Initial revision
by
Olin Lathrop
·
2020-07-14T22:16:42Z (almost 4 years ago)
All the proposals so far are missing what people really want to know, which are two orthogonal metrics:<ol> <li>How good/bad the crowd thinks the answer is. <li>How heavily the crowd has weighed in. </ol> The first tells you how much to believe the answer, and the second how much to believe the first point. Put another way, you want to see a score and how big the error band is for that score. So lets show that. The obvious formula for #1 is (up votes) / (total votes). I'd multiply that by 100 then round to the nearest integer. Values from 0-100 are easier to explain than 0.0 to 1.0. You don't really need to know the difference between 98.2 and 98.4, so keep it simple. There are more choices how to present the confidence, but the total number of votes is a really simple value. We could get into probability, gaussian distribution assumptions, standard deviations, and the like, but too many people won't understand that and just tune out. <h3>Examples</h3> +5, -3: <b>Score 63, votes 8</b> +20, -15: <b>Score 57, votes 35</b> +0, -0: <b>Votes 0</b> +0, -3: <b>Score 0, votes 3</b> I would display the 0-100 score most prominently, probably without a label, then the number of votes below that in smaller font with a label.