if a sequence of distributions converges to a degenerate, does that mean that variance decreases? when the min of a draws from f$ decreases mean if the variance of f_i is a degenerate, does the mean decrease? which condition of a kumaraswamy distribution is true? does the variance decrease in a kumaranaswamy distribution why does variance decrease in the kupupalaswamy distribution if a sequence of distributions converges to a degenerate distribution, does that imply that the variance of $f_i$ strictly decreases? if a sequence of distributions converges to a degenerate distribution do the mean and variance decreases? when f_0 increases variance when the min of the distribution decreases does the variance decrease with the min of a draw from the distribution of the min of a drawn from the distribution of the min of b drawn what is the cdf of the min of the f distribution if a sequence of distributions converges to a degenerate distribution, does that mean that the variance of $i$ decreases with the distribution of $i is variance decreased by the sum of min and max what is the difference between a sum of min, and variance? does a sequence of distributions converge to a degenerate distribution? if a sequence of distributions converges to a degenerate, does that imply that the variance strictly decreases what does it mean when variance increases? why do kravanaswamy distributions decrease in inverse does variance decrease for kumaraswamy