The standard deviation is the square root of the variance standard deviation tends to be more directly useful (although both are used, depending on what you're doing with the numbers). Variance is a measure of how wide the distribution of results is specifically, if the expected value is M and x is the random variable, variance is the expected value of ( M- x)^2. Expected value (or expectation) is just a fancy way of saying 'average' of a random variable. Let's start with the basics: expected value, variance, and standard deviation. This one will probably be heavier on the math than the rest, if only because it's needed to set the stage.) (Yes, there will be math, though I'll try not to push into eyes-glaze-over territory. But I'm much more of a math and statistics person than an Xs-and-Os guy, so these will be devoted to statistical analysis and game theory. ' series on Xs-and-Os strategy, I've decided to post some strategy articles of my own. The offseason is upon us, and in the tradition of Heck's 'Better Know A.
