If you ever have a free hour, check out the wikipedia page for regression analysis.<p><a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Regression_analysis" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Regression_analysis</a><p>It&#x27;s by far the most approachable wikipedia page&#x2F;section I&#x27;ve encountered for explaining a mathematical topic.<p>Regression analysis has a few things going for it over other topics.<p>1) It uses simple math.  We aren&#x27;t solving black scholes here and using Ito&#x27;s lema.  All the math you need to do least square regression you learned in high school.<p>2) Its graph-able.  Some people are fine learning via numbers only, some people need to visualize the result.  For the later, being able to show a line going through a series of points makes analysis super easy.<p>A few weeks ago my 7 year old daughter saw an R kniter doc with a grid of 25 plots on I was using for determining co-integration of various ETF&#x27;s for the purpose of pairs trading.<p>She doesn&#x27;t obviously understand linear regression though she was able to look at the plots and find the ones who had the best &quot;fit&quot;.<p>2b) The results are dead simple in most cases to interpret.<p>I think one thing that trips people up with statistics is that up until they encounter statistics, most of the math they are introduced to is analytical, you take the  numbers, apply the formula and get a definitive answer.<p>Then you encounter statistics and realize there is no black and white, you can get an average, but what about its standard deviation?  Ok, now you have to analyze the standard deviation, and repeat to infinity.<p>You never really get a definitive, &quot;this is the answer&quot; style answer from statistics.  Everything is &quot;here is your result, but you should also apply this technique to analyze your result&quot;.<p>With linear regression, its often very simple to interpret your results, which makes it one of the more approachable statistical techniques.<p>3) It has well supported libraries in almost any programming language.