| > | restart: read `C:\\Tanis-Hogg\\Maple Examples\\stat.m`: |
Elliot Tanis
April 20, 2006
Exercise 5.3-4 (Exercise_5_3-4.mws)
| > | f := 2*x; |
| > | mu := int(x*f, x = 0 .. 1); evalf(%); |
| > | var := int((x - mu)^2*f, x = 0 .. 1); evalf(%); sigma := evalf(sqrt(var)); |
| > | for j from 1 to 1000 do for k from 1 to 18 do XX[k] := evalf(sqrt(rng())): od: X := [seq(XX[k], k = 1 .. 18)]: Xbar[j] := Mean(X): od: Xbars := [seq(Xbar[j], j = 1 .. 1000)]: |
| > | Mean(Xbars); |
| > | Variance(Xbars); |
| > | evalf(var/18); |
| > | Min(Xbars), Max(Xbars); |
Now construct a histogram with a N (2/3, (1/18)/18) p.d.f. superimposed.
| > | xtics := [seq(0.4 + k*0.05, k = 0 .. 10)]: ytics := [seq(0.5*k, k = 1 .. 15)]: P1 := plot(NormalPDF(mu, var/18, x), x = 0.4 .. 0.9,y = 0 .. 7.7, color=black, thickness=2, xtickmarks=xtics, ytickmarks=ytics, labels=[``,``]): P2 := HistogramFill(Xbars, 0.40 .. 0.90, 20): display({P1, P2}); |
| > |