A "factoid" is a nonexistent word invented by CNN and expropriated here
as just the right nonword for the situation.
Frequentists and Bayesians - There is a continuing debate among
statisticians over the proper definition of "probability."
"Probabilistics" - There is more to Monte Carlo simulation than
replacing constants with probability densities.
Bivariate Normal - Here is a simple algorithm for sampling from a
bivariate normal distribution.
Goodness-of-Fit Goodness-of-Fit tests, like Anderson-Darling, tell you
when you
don't have a normal distribution.
R-squared ... is an often misused goodness-of-fit metric, where bigger
isn't always better.
Other Measures R-squared isn't the only way to judge how well the model
works.
Curse of Dimensionality Direct-sampling Monte Carlo requires the number
of samples per variable to increase exponentially with the number of
variables to maintain a given level of accuracy.
convergence in distribution - We engineers are familiar with convergence
to a point, but what of convergence to a distribution?
extreme value distributions - The largest, or smallest, observation in a
sample has one of three possible distributions. This is another example of
"convergence in distribution."
Bayesian Updating - We use Bayesian Statistics every day without knowing
it.
Sums of Random Variables - Sometimes you need to know the distribution
of some combination of things. Here's an example.
Distributional Inter-relationships - There are myriad probability
distributions. But did you know that most are related to one another, and
ultimately related to the Normal?
Bootstrapping - Bootstrap and Jackknife algorithms don't really give you
something for nothing. They give you something you previously ignored.
Bartlett correction (external link) - A Bartlett correction is a scalar
transformation applied to the likelihood ratio statistic that yields an
improved test statistic with chi-squared null distribution of order O(1/n),
as compared with order O(1) for the LR.