Ways to fix statistics
I consider myself analytically-minded, and statistics still gives me a headache. Most people understand basic relationships: &quot;These numbers are different, but not meaningfully so&quot; or, &quot;These two elements are more strongly related than these other two.&quot;<p>The problem is threefold:<p>1. <i>Learning statistics is a tautology.</i> Meaning: the best way to learn statistics is to already know statistics. Go google how to do basic significance calculations in, say, Excel. The <i>first</i> paragraph of the resulting articles will dive into t-test and twin-tales and P-values and on down the lines. Ask someone how to do a simple comparison, and they&#x27;ll digress into null hypotheses and &quot;what test did you decide to run&quot;. You&#x27;ll probably see some nasty formulas and opining about which PhD-level approach is better. It&#x27;s just opaque.<p>2. <i>Tools are professional grade.</i> Software needs to bridge the gap between users&#x27; intent and their ability to do the analysis. Statistics requires R (you have to know how to program <i>and</i> statistics), SAS ($$$), or another package that limits barrier to entry. Most people know how to ask the basic question, but no idea how to get the answer or interpret the results.<p>3. <i>People who know statistics can&#x27;t interpret results to laymen.</i> I see this a lot in business: really bright folks build segmentation models and predictive models, you start talking about cohorts and medians... but that&#x27;s where it ends. Your c-suite doesn&#x27;t care about that: it cares about the so-what.