In general, the Central Limit Theorem gives a better estimate than Chebyshev's inequality for the average of a sum. To see this, let A25 be the average calculated in Exercise 5, and let N be the normal approximation for A25. Modify your program in Exercise 5 to provide a table of the function F(x)=P(∣A25−10∣≥x)= fraction of the total of 1000 trials for which ∣A25−10∣≥x. Do the same for the function f(x)=P(∣N−10∣≥x). (You can use the normal table, Table 9.4, or the procedure NormalArea for this.) Now plot on the same axes the graphs of F(x), f(x), and the Chebyshev function g(x)=4/(3x2). How do f(x) and g(x) compare as estimates for F(x)?