Community RSS Feed https://community.wolfram.com RSS Feed for Wolfram Community showing any discussions in tag Statistics and Probability sorted by active Simulating "Animal Crossing: New Horizons" Mendelian Flower Genetics https://community.wolfram.com/groups/-/m/t/2174471 &amp;[Wolfram Notebook] : https://www.wolframcloud.com/obj/33d543ff-cefe-4461-866b-3b3436833330 Pedro Cabral 2021-01-26T01:52:51Z Strange PDF of BinomialDistribution https://community.wolfram.com/groups/-/m/t/2164818 PDF[BinomialDistribution[1,.5],{0,0.5,1}] gives {0.5,0.63662,0.5} and PDF[BernoulliDistribution[.5],{0,0.5,1}] gives {0.5,0,0.5}. Obviously, BinomialDistribution[1,.5] and BernoulliDistribution[.5] are the same. Stefan Huschens 2021-01-16T13:30:03Z Calculation of variance of weighted data https://community.wolfram.com/groups/-/m/t/2172718 The WDC example ([/Scope/Data]: &#034;Find the variance of WeightedData&#034;) merges the internal intermediary result (of the mean) and shows the end result in a single line only, so i cannot back track anymore. Inspired by that WDC example, please could anyone demonstrate how the $\frac{8800}{23}$ was calculated (just the start/from which definition)? Feel free to use two lines: 1 line for the numeric mean, 1 for the variance using that numeric mean. In:= data = {-30, 10, 10, 10, 10, 10, 10, 10, 20, 20};(* sample data *) {Mean[data], Variance[data]}(* bias-corrected sample variance*) Out= {8, 1760/9} In:= edis = EmpiricalDistribution[data];(* population *) {Mean[edis], Variance[edis]}(* population variance *) Out= {8, 176} In:= wdata = WeightedData[{-30, 10, 20}, {1/10, 7/10, 2/10}]; wedis = EmpiricalDistribution[wdata]; {Mean[wedis], Variance[wedis]}(* okay,as expected *) Out= {8, 176} In:= {Mean[wdata], Variance[wdata]}(* which formula/definition used here, why? *) Out= {8, 8800/23} I cannot figure it out, thank you! Best wishes. : https://reference.wolfram.com/language/ref/Variance.html Raspi Rascal 2021-01-24T18:34:40Z VARIANCE and PDF https://community.wolfram.com/groups/-/m/t/2169540 Hello all, I am struggling to find the correct function for Variance. It does exist, but it is the SAMPLE variance, i.e. the (n-1) denominator. I need to find (if it does exist) the SIGMA variance, i.e. the one with just N at the denominator. Anyone knows ? Plus, suppose I wanted to plot the pdf f(x) =ce^-x (0&lt;x&lt;1) and find the CDF and its expected value. How would I proceed? Thank you all. Mauro Benjamin Mistretta 2021-01-21T19:50:36Z