Statistics/Basic: Difference between revisions

=={{header|Phix}}==

{{trans|CoffeeScript}}

To do a trillion samples, I would change the existing generate loop into an inner 100_000_000 loop that still uses the fast native types, with everything outside that changed to bigatom, and of course add an outer loop which sums into them.

<lang Phix>function generate_statistics(integer n)

sequence hist = repeat(0,10)

atom sum_r = 0,

sum_squares = 0.0

for i=1 to n do

atom r = rnd()

sum_r += r

sum_squares += r*r

hist[floor(10*r)+1] += 1

end for

atom mean = sum_r / n

atom stddev = sqrt((sum_squares / n) - mean*mean)

return {n, mean, stddev, hist}

end function

procedure display_statistics(sequence x)

atom n, mean, stddev

sequence hist

{n, mean, stddev, hist} = x

printf(1,"-- Stats for sample size %d\n",{n})

printf(1,"mean: %g\n",{mean})

printf(1,"sdev: %g\n",{stddev})

for i=1 to length(hist) do

integer cnt = hist[i]

string bars = repeat('=',floor(cnt*300/n))

printf(1,"%.1f: %s %d\n",{i/10,bars,cnt})

end for

end procedure

for n=2 to 5 do

display_statistics(generate_statistics(power(10,n+(n=5))))

end for</lang>

{{Out}}

<pre style="float:left; font-size: 10px">

-- Stats for sample size 100

mean: 0.530925

sdev: 0.303564

0.1: ======================== 8

0.2: ======================================= 13

0.3: ============================== 10

0.4: ================== 6

0.5: ===================== 7

0.6: ================================= 11

0.7: ================================= 11

0.8: ===================== 7

0.9: ======================================= 13

1.0: ========================================== 14

</pre>

<pre style="float:left; font-size: 10px">

-- Stats for sample size 1000

mean: 0.50576

sdev: 0.288862

0.1: ============================ 95

0.2: ============================== 103

0.3: ============================= 98

0.4: =========================== 93

0.5: ============================== 101

0.6: ============================= 99

0.7: =============================== 105

0.8: ============================= 97

0.9: ================================ 108

1.0: ============================== 101

</pre>

<pre style="float:left; font-size: 10px">

-- Stats for sample size 10000

mean: 0.498831

sdev: 0.28841

0.1: ============================= 987

0.2: =============================== 1060

0.3: ============================ 953

0.4: ============================= 980

0.5: ============================== 1013

0.6: ============================= 997

0.7: ================================ 1089

0.8: ============================ 948

0.9: ============================= 974

1.0: ============================= 999

</pre>

<pre style="font-size: 10px">

-- Stats for sample size 1000000

mean: 0.499937

sdev: 0.288898

0.1: ============================== 100071

0.2: ============================== 100943

0.3: ============================= 99594

0.4: ============================= 99436

0.5: ============================= 99806

0.6: ============================= 99723

0.7: ============================== 100040

0.8: ============================== 100280

0.9: ============================== 100264

1.0: ============================= 99843

</pre>