## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_rngnorm.wasp
Title produced by softwareRandom Number Generator - Normal Distribution
Date of computationFri, 10 Apr 2020 02:43:32 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Apr/10/t1586479766u4ggkzkpflmmcik.htm/, Retrieved Fri, 07 May 2021 10:24:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319125, Retrieved Fri, 07 May 2021 10:24:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact44
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Random Number Generator - Normal Distribution] [] [2020-04-10 00:43:32] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319125&T=0

[TABLE]
[ROW]
 Summary of computational transaction[/C][/ROW] [ROW] Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW] Raw Output[/C] view raw output of R engine [/C][/ROW] [ROW] Computing time[/C] 1 seconds[/C][/ROW] [ROW] R Server[/C] Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319125&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319125&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server Big Analytics Cloud Computing Center

 Index Value 1 75.9092804453138 2 99.9456089671074 3 81.2242541553456 4 78.0837372670532 5 72.0509536961266 6 82.7747244338927 7 83.179703848005 8 77.5786906936765 9 78.4448931156834 10 81.8379732683898 11 56.7786284716642 12 70.3463064924373 13 59.7026675254469 14 60.3112841365525 15 67.0458894992853 16 78.3398099381745 17 86.4480541526368 18 63.3852902124498 19 69.9578775635292 20 58.8737577118339 21 69.8903929378792 22 88.1855456093195 23 73.9682823594305 24 56.8900655645724 25 73.3169494121499 26 70.4442103764379 27 81.6449583308727 28 74.96604381706 29 83.9899348889593 30 94.6501974402377 31 53.4868033178207 32 67.5479371718511 33 79.5877704371873 34 70.7798639050472 35 94.5781253079903 36 70.098487236775 37 72.2210049569569 38 70.3121350292134 39 78.2320254951666 40 87.2502161486681 41 67.6243991541122 42 83.579773756041 43 85.2296784426842 44 72.7809317424319 45 70.4307383399063 46 69.9988355944956 47 70.4151938564693 48 81.3628275464728 49 71.314508629553 50 73.3707816822033 51 95.7354493773599 52 72.4960776375178 53 68.522700535719 54 69.1349777359455 55 65.3854373709824 56 72.6294319803419 57 67.7491548476606 58 74.3951137456236 59 77.6776382937645 60 64.5596863267669 61 73.9870541499874 62 72.0598418416971 63 93.5604754920478 64 73.8073890419459 65 72.6792924252857 66 73.8378753802055 67 74.0342881112849 68 91.9285440918423 69 81.8052080858761 70 48.3809389490868 71 69.1389616132499 72 79.6504847321554 73 58.6409016547198 74 68.9626749028615 75 75.0435282836942 76 99.9337009385647 77 81.9894449862901 78 60.5345600798945 79 79.4456704957112 80 76.5393044302675 81 56.9312372493051 82 88.4222239714756 83 72.569960494379 84 79.2853667822798 85 66.8549127820294 86 72.7536946621327 87 68.8599500849886 88 85.2252870971181 89 61.6827729192674 90 54.733454880067 91 66.9260750175453 92 77.3071252128979 93 74.4349691499433 94 77.3490228218381 95 66.3739175138002 96 65.2219456065528 97 77.7495707092029 98 85.5002160860351 99 84.4409794287261 100 71.0428936799963

\begin{tabular}{lllllllll}
\hline
Index & Value \tabularnewline
1 & 75.9092804453138 \tabularnewline
2 & 99.9456089671074 \tabularnewline
3 & 81.2242541553456 \tabularnewline
4 & 78.0837372670532 \tabularnewline
5 & 72.0509536961266 \tabularnewline
6 & 82.7747244338927 \tabularnewline
7 & 83.179703848005 \tabularnewline
8 & 77.5786906936765 \tabularnewline
9 & 78.4448931156834 \tabularnewline
10 & 81.8379732683898 \tabularnewline
11 & 56.7786284716642 \tabularnewline
12 & 70.3463064924373 \tabularnewline
13 & 59.7026675254469 \tabularnewline
14 & 60.3112841365525 \tabularnewline
15 & 67.0458894992853 \tabularnewline
16 & 78.3398099381745 \tabularnewline
17 & 86.4480541526368 \tabularnewline
18 & 63.3852902124498 \tabularnewline
19 & 69.9578775635292 \tabularnewline
20 & 58.8737577118339 \tabularnewline
21 & 69.8903929378792 \tabularnewline
22 & 88.1855456093195 \tabularnewline
23 & 73.9682823594305 \tabularnewline
24 & 56.8900655645724 \tabularnewline
25 & 73.3169494121499 \tabularnewline
26 & 70.4442103764379 \tabularnewline
27 & 81.6449583308727 \tabularnewline
28 & 74.96604381706 \tabularnewline
29 & 83.9899348889593 \tabularnewline
30 & 94.6501974402377 \tabularnewline
31 & 53.4868033178207 \tabularnewline
32 & 67.5479371718511 \tabularnewline
33 & 79.5877704371873 \tabularnewline
34 & 70.7798639050472 \tabularnewline
35 & 94.5781253079903 \tabularnewline
36 & 70.098487236775 \tabularnewline
37 & 72.2210049569569 \tabularnewline
38 & 70.3121350292134 \tabularnewline
39 & 78.2320254951666 \tabularnewline
40 & 87.2502161486681 \tabularnewline
41 & 67.6243991541122 \tabularnewline
42 & 83.579773756041 \tabularnewline
43 & 85.2296784426842 \tabularnewline
44 & 72.7809317424319 \tabularnewline
45 & 70.4307383399063 \tabularnewline
46 & 69.9988355944956 \tabularnewline
47 & 70.4151938564693 \tabularnewline
48 & 81.3628275464728 \tabularnewline
49 & 71.314508629553 \tabularnewline
50 & 73.3707816822033 \tabularnewline
51 & 95.7354493773599 \tabularnewline
52 & 72.4960776375178 \tabularnewline
53 & 68.522700535719 \tabularnewline
54 & 69.1349777359455 \tabularnewline
55 & 65.3854373709824 \tabularnewline
56 & 72.6294319803419 \tabularnewline
57 & 67.7491548476606 \tabularnewline
58 & 74.3951137456236 \tabularnewline
59 & 77.6776382937645 \tabularnewline
60 & 64.5596863267669 \tabularnewline
61 & 73.9870541499874 \tabularnewline
62 & 72.0598418416971 \tabularnewline
63 & 93.5604754920478 \tabularnewline
64 & 73.8073890419459 \tabularnewline
65 & 72.6792924252857 \tabularnewline
66 & 73.8378753802055 \tabularnewline
67 & 74.0342881112849 \tabularnewline
68 & 91.9285440918423 \tabularnewline
69 & 81.8052080858761 \tabularnewline
70 & 48.3809389490868 \tabularnewline
71 & 69.1389616132499 \tabularnewline
72 & 79.6504847321554 \tabularnewline
73 & 58.6409016547198 \tabularnewline
74 & 68.9626749028615 \tabularnewline
75 & 75.0435282836942 \tabularnewline
76 & 99.9337009385647 \tabularnewline
77 & 81.9894449862901 \tabularnewline
78 & 60.5345600798945 \tabularnewline
79 & 79.4456704957112 \tabularnewline
80 & 76.5393044302675 \tabularnewline
81 & 56.9312372493051 \tabularnewline
82 & 88.4222239714756 \tabularnewline
83 & 72.569960494379 \tabularnewline
84 & 79.2853667822798 \tabularnewline
85 & 66.8549127820294 \tabularnewline
86 & 72.7536946621327 \tabularnewline
87 & 68.8599500849886 \tabularnewline
88 & 85.2252870971181 \tabularnewline
89 & 61.6827729192674 \tabularnewline
90 & 54.733454880067 \tabularnewline
91 & 66.9260750175453 \tabularnewline
92 & 77.3071252128979 \tabularnewline
93 & 74.4349691499433 \tabularnewline
94 & 77.3490228218381 \tabularnewline
95 & 66.3739175138002 \tabularnewline
96 & 65.2219456065528 \tabularnewline
97 & 77.7495707092029 \tabularnewline
98 & 85.5002160860351 \tabularnewline
99 & 84.4409794287261 \tabularnewline
100 & 71.0428936799963 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319125&T=1

[TABLE]
[ROW][C]Index[/C][C]Value[/C][/ROW]
[ROW][C]1[/C][C]75.9092804453138[/C][/ROW]
[ROW][C]2[/C][C]99.9456089671074[/C][/ROW]
[ROW][C]3[/C][C]81.2242541553456[/C][/ROW]
[ROW][C]4[/C][C]78.0837372670532[/C][/ROW]
[ROW][C]5[/C][C]72.0509536961266[/C][/ROW]
[ROW][C]6[/C][C]82.7747244338927[/C][/ROW]
[ROW][C]7[/C][C]83.179703848005[/C][/ROW]
[ROW][C]8[/C][C]77.5786906936765[/C][/ROW]
[ROW][C]9[/C][C]78.4448931156834[/C][/ROW]
[ROW][C]10[/C][C]81.8379732683898[/C][/ROW]
[ROW][C]11[/C][C]56.7786284716642[/C][/ROW]
[ROW][C]12[/C][C]70.3463064924373[/C][/ROW]
[ROW][C]13[/C][C]59.7026675254469[/C][/ROW]
[ROW][C]14[/C][C]60.3112841365525[/C][/ROW]
[ROW][C]15[/C][C]67.0458894992853[/C][/ROW]
[ROW][C]16[/C][C]78.3398099381745[/C][/ROW]
[ROW][C]17[/C][C]86.4480541526368[/C][/ROW]
[ROW][C]18[/C][C]63.3852902124498[/C][/ROW]
[ROW][C]19[/C][C]69.9578775635292[/C][/ROW]
[ROW][C]20[/C][C]58.8737577118339[/C][/ROW]
[ROW][C]21[/C][C]69.8903929378792[/C][/ROW]
[ROW][C]22[/C][C]88.1855456093195[/C][/ROW]
[ROW][C]23[/C][C]73.9682823594305[/C][/ROW]
[ROW][C]24[/C][C]56.8900655645724[/C][/ROW]
[ROW][C]25[/C][C]73.3169494121499[/C][/ROW]
[ROW][C]26[/C][C]70.4442103764379[/C][/ROW]
[ROW][C]27[/C][C]81.6449583308727[/C][/ROW]
[ROW][C]28[/C][C]74.96604381706[/C][/ROW]
[ROW][C]29[/C][C]83.9899348889593[/C][/ROW]
[ROW][C]30[/C][C]94.6501974402377[/C][/ROW]
[ROW][C]31[/C][C]53.4868033178207[/C][/ROW]
[ROW][C]32[/C][C]67.5479371718511[/C][/ROW]
[ROW][C]33[/C][C]79.5877704371873[/C][/ROW]
[ROW][C]34[/C][C]70.7798639050472[/C][/ROW]
[ROW][C]35[/C][C]94.5781253079903[/C][/ROW]
[ROW][C]36[/C][C]70.098487236775[/C][/ROW]
[ROW][C]37[/C][C]72.2210049569569[/C][/ROW]
[ROW][C]38[/C][C]70.3121350292134[/C][/ROW]
[ROW][C]39[/C][C]78.2320254951666[/C][/ROW]
[ROW][C]40[/C][C]87.2502161486681[/C][/ROW]
[ROW][C]41[/C][C]67.6243991541122[/C][/ROW]
[ROW][C]42[/C][C]83.579773756041[/C][/ROW]
[ROW][C]43[/C][C]85.2296784426842[/C][/ROW]
[ROW][C]44[/C][C]72.7809317424319[/C][/ROW]
[ROW][C]45[/C][C]70.4307383399063[/C][/ROW]
[ROW][C]46[/C][C]69.9988355944956[/C][/ROW]
[ROW][C]47[/C][C]70.4151938564693[/C][/ROW]
[ROW][C]48[/C][C]81.3628275464728[/C][/ROW]
[ROW][C]49[/C][C]71.314508629553[/C][/ROW]
[ROW][C]50[/C][C]73.3707816822033[/C][/ROW]
[ROW][C]51[/C][C]95.7354493773599[/C][/ROW]
[ROW][C]52[/C][C]72.4960776375178[/C][/ROW]
[ROW][C]53[/C][C]68.522700535719[/C][/ROW]
[ROW][C]54[/C][C]69.1349777359455[/C][/ROW]
[ROW][C]55[/C][C]65.3854373709824[/C][/ROW]
[ROW][C]56[/C][C]72.6294319803419[/C][/ROW]
[ROW][C]57[/C][C]67.7491548476606[/C][/ROW]
[ROW][C]58[/C][C]74.3951137456236[/C][/ROW]
[ROW][C]59[/C][C]77.6776382937645[/C][/ROW]
[ROW][C]60[/C][C]64.5596863267669[/C][/ROW]
[ROW][C]61[/C][C]73.9870541499874[/C][/ROW]
[ROW][C]62[/C][C]72.0598418416971[/C][/ROW]
[ROW][C]63[/C][C]93.5604754920478[/C][/ROW]
[ROW][C]64[/C][C]73.8073890419459[/C][/ROW]
[ROW][C]65[/C][C]72.6792924252857[/C][/ROW]
[ROW][C]66[/C][C]73.8378753802055[/C][/ROW]
[ROW][C]67[/C][C]74.0342881112849[/C][/ROW]
[ROW][C]68[/C][C]91.9285440918423[/C][/ROW]
[ROW][C]69[/C][C]81.8052080858761[/C][/ROW]
[ROW][C]70[/C][C]48.3809389490868[/C][/ROW]
[ROW][C]71[/C][C]69.1389616132499[/C][/ROW]
[ROW][C]72[/C][C]79.6504847321554[/C][/ROW]
[ROW][C]73[/C][C]58.6409016547198[/C][/ROW]
[ROW][C]74[/C][C]68.9626749028615[/C][/ROW]
[ROW][C]75[/C][C]75.0435282836942[/C][/ROW]
[ROW][C]76[/C][C]99.9337009385647[/C][/ROW]
[ROW][C]77[/C][C]81.9894449862901[/C][/ROW]
[ROW][C]78[/C][C]60.5345600798945[/C][/ROW]
[ROW][C]79[/C][C]79.4456704957112[/C][/ROW]
[ROW][C]80[/C][C]76.5393044302675[/C][/ROW]
[ROW][C]81[/C][C]56.9312372493051[/C][/ROW]
[ROW][C]82[/C][C]88.4222239714756[/C][/ROW]
[ROW][C]83[/C][C]72.569960494379[/C][/ROW]
[ROW][C]84[/C][C]79.2853667822798[/C][/ROW]
[ROW][C]85[/C][C]66.8549127820294[/C][/ROW]
[ROW][C]86[/C][C]72.7536946621327[/C][/ROW]
[ROW][C]87[/C][C]68.8599500849886[/C][/ROW]
[ROW][C]88[/C][C]85.2252870971181[/C][/ROW]
[ROW][C]89[/C][C]61.6827729192674[/C][/ROW]
[ROW][C]90[/C][C]54.733454880067[/C][/ROW]
[ROW][C]91[/C][C]66.9260750175453[/C][/ROW]
[ROW][C]92[/C][C]77.3071252128979[/C][/ROW]
[ROW][C]93[/C][C]74.4349691499433[/C][/ROW]
[ROW][C]94[/C][C]77.3490228218381[/C][/ROW]
[ROW][C]95[/C][C]66.3739175138002[/C][/ROW]
[ROW][C]96[/C][C]65.2219456065528[/C][/ROW]
[ROW][C]97[/C][C]77.7495707092029[/C][/ROW]
[ROW][C]98[/C][C]85.5002160860351[/C][/ROW]
[ROW][C]99[/C][C]84.4409794287261[/C][/ROW]
[ROW][C]100[/C][C]71.0428936799963[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319125&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319125&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Index Value 1 75.9092804453138 2 99.9456089671074 3 81.2242541553456 4 78.0837372670532 5 72.0509536961266 6 82.7747244338927 7 83.179703848005 8 77.5786906936765 9 78.4448931156834 10 81.8379732683898 11 56.7786284716642 12 70.3463064924373 13 59.7026675254469 14 60.3112841365525 15 67.0458894992853 16 78.3398099381745 17 86.4480541526368 18 63.3852902124498 19 69.9578775635292 20 58.8737577118339 21 69.8903929378792 22 88.1855456093195 23 73.9682823594305 24 56.8900655645724 25 73.3169494121499 26 70.4442103764379 27 81.6449583308727 28 74.96604381706 29 83.9899348889593 30 94.6501974402377 31 53.4868033178207 32 67.5479371718511 33 79.5877704371873 34 70.7798639050472 35 94.5781253079903 36 70.098487236775 37 72.2210049569569 38 70.3121350292134 39 78.2320254951666 40 87.2502161486681 41 67.6243991541122 42 83.579773756041 43 85.2296784426842 44 72.7809317424319 45 70.4307383399063 46 69.9988355944956 47 70.4151938564693 48 81.3628275464728 49 71.314508629553 50 73.3707816822033 51 95.7354493773599 52 72.4960776375178 53 68.522700535719 54 69.1349777359455 55 65.3854373709824 56 72.6294319803419 57 67.7491548476606 58 74.3951137456236 59 77.6776382937645 60 64.5596863267669 61 73.9870541499874 62 72.0598418416971 63 93.5604754920478 64 73.8073890419459 65 72.6792924252857 66 73.8378753802055 67 74.0342881112849 68 91.9285440918423 69 81.8052080858761 70 48.3809389490868 71 69.1389616132499 72 79.6504847321554 73 58.6409016547198 74 68.9626749028615 75 75.0435282836942 76 99.9337009385647 77 81.9894449862901 78 60.5345600798945 79 79.4456704957112 80 76.5393044302675 81 56.9312372493051 82 88.4222239714756 83 72.569960494379 84 79.2853667822798 85 66.8549127820294 86 72.7536946621327 87 68.8599500849886 88 85.2252870971181 89 61.6827729192674 90 54.733454880067 91 66.9260750175453 92 77.3071252128979 93 74.4349691499433 94 77.3490228218381 95 66.3739175138002 96 65.2219456065528 97 77.7495707092029 98 85.5002160860351 99 84.4409794287261 100 71.0428936799963

 Frequency Table (Histogram) Bins Midpoint Abs. Frequency Rel. Frequency Cumul. Rel. Freq. Density [45,50[ 47.5 1 0.01 0.01 0.002 [50,55[ 52.5 2 0.02 0.03 0.004 [55,60[ 57.5 6 0.06 0.09 0.012 [60,65[ 62.5 5 0.05 0.14 0.01 [65,70[ 67.5 17 0.17 0.31 0.034 [70,75[ 72.5 28 0.28 0.59 0.056 [75,80[ 77.5 16 0.16 0.75 0.032 [80,85[ 82.5 11 0.11 0.86 0.022 [85,90[ 87.5 7 0.07 0.93 0.014 [90,95[ 92.5 4 0.04 0.97 0.008 [95,100] 97.5 3 0.03 1 0.006

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[45,50[ & 47.5 & 1 & 0.01 & 0.01 & 0.002 \tabularnewline
[50,55[ & 52.5 & 2 & 0.02 & 0.03 & 0.004 \tabularnewline
[55,60[ & 57.5 & 6 & 0.06 & 0.09 & 0.012 \tabularnewline
[60,65[ & 62.5 & 5 & 0.05 & 0.14 & 0.01 \tabularnewline
[65,70[ & 67.5 & 17 & 0.17 & 0.31 & 0.034 \tabularnewline
[70,75[ & 72.5 & 28 & 0.28 & 0.59 & 0.056 \tabularnewline
[75,80[ & 77.5 & 16 & 0.16 & 0.75 & 0.032 \tabularnewline
[80,85[ & 82.5 & 11 & 0.11 & 0.86 & 0.022 \tabularnewline
[85,90[ & 87.5 & 7 & 0.07 & 0.93 & 0.014 \tabularnewline
[90,95[ & 92.5 & 4 & 0.04 & 0.97 & 0.008 \tabularnewline
[95,100] & 97.5 & 3 & 0.03 & 1 & 0.006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319125&T=2

[TABLE]
[ROW][C]Frequency Table (Histogram)[/C][/ROW]
[ROW][C]Bins[/C][C]Midpoint[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][C]Cumul. Rel. Freq.[/C][C]Density[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]1[/C][C]0.01[/C][C]0.01[/C][C]0.002[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]2[/C][C]0.02[/C][C]0.03[/C][C]0.004[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]6[/C][C]0.06[/C][C]0.09[/C][C]0.012[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]5[/C][C]0.05[/C][C]0.14[/C][C]0.01[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]17[/C][C]0.17[/C][C]0.31[/C][C]0.034[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]28[/C][C]0.28[/C][C]0.59[/C][C]0.056[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]16[/C][C]0.16[/C][C]0.75[/C][C]0.032[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]11[/C][C]0.11[/C][C]0.86[/C][C]0.022[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]7[/C][C]0.07[/C][C]0.93[/C][C]0.014[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]4[/C][C]0.04[/C][C]0.97[/C][C]0.008[/C][/ROW]
[ROW][C][95,100][/C][C]97.5[/C][C]3[/C][C]0.03[/C][C]1[/C][C]0.006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319125&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319125&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Frequency Table (Histogram) Bins Midpoint Abs. Frequency Rel. Frequency Cumul. Rel. Freq. Density [45,50[ 47.5 1 0.01 0.01 0.002 [50,55[ 52.5 2 0.02 0.03 0.004 [55,60[ 57.5 6 0.06 0.09 0.012 [60,65[ 62.5 5 0.05 0.14 0.01 [65,70[ 67.5 17 0.17 0.31 0.034 [70,75[ 72.5 28 0.28 0.59 0.056 [75,80[ 77.5 16 0.16 0.75 0.032 [80,85[ 82.5 11 0.11 0.86 0.022 [85,90[ 87.5 7 0.07 0.93 0.014 [90,95[ 92.5 4 0.04 0.97 0.008 [95,100] 97.5 3 0.03 1 0.006

par8 <- '100'par7 <- '0'par6 <- '0'par5 <- 'N'par4 <- '2'par3 <- '10'par2 <- '075'par1 <- '100'library(MASS)library(msm)par1 <- sub(',','.',par1)par2 <- sub(',','.',par2)par3 <- sub(',','.',par3)par4 <- sub(',','.',par4)par1 <- as.numeric(par1)if (par1 > 10000) par1=10000 #impose restriction on number of random valuespar2 <- as.numeric(par2)par3 <- as.numeric(par3)par4 <- as.numeric(par4)if (par6 == '0') par6 = 'Sturges' else {par6 <- as.numeric(par6)if (par6 > 50) par6 = 50 #impose restriction on the number of bins}if (par7 == '') par7 <- -Inf else par7 <- as.numeric(par7)if (par8 == '') par8 <- Inf else par8 <- as.numeric(par8)x <- rtnorm(par1,par2,par3,par7,par8)x <- as.ts(x) #otherwise the fitdistr function does not work properlyif ((par7 == -Inf) & (par8 == Inf)) (r <- fitdistr(x,'normal'))bitmap(file='test1.png')myhist<-hist(x,col=par4,breaks=par6,main=main,ylab=ylab,xlab=xlab,freq=F)if ((par7 == -Inf) & (par8 == Inf)) {curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T)}dev.off()load(file='createtable')if (par5 == 'Y'){a<-table.start()a<-table.row.start(a)a<-table.element(a,'Index',1,TRUE)a<-table.element(a,'Value',1,TRUE)a<-table.row.end(a)for (i in 1:par1){a<-table.row.start(a)a<-table.element(a,i,header=TRUE)a<-table.element(a,x[i])a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable1.tab')}if ((par7 == -Inf) & (par8 == Inf)) {a<-table.start()a<-table.row.start(a)a<-table.element(a,'Parameter',1,TRUE)a<-table.element(a,'Value',1,TRUE)a<-table.element(a,'Standard Deviation',1,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'# simulated values',header=TRUE)a<-table.element(a,par1)a<-table.element(a,'-')a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'true mean',header=TRUE)a<-table.element(a,par2)a<-table.element(a,'-')a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'true standard deviation',header=TRUE)a<-table.element(a,par3)a<-table.element(a,'-')a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'mean',header=TRUE)a<-table.element(a,r$estimate[1])a<-table.element(a,r$sd[1])a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'standard deviation',header=TRUE)a<-table.element(a,r$estimate[2])a<-table.element(a,r$sd[2])a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable.tab')}a<-table.start()a<-table.row.start(a)a<-table.element(a,'Frequency Table (Histogram)',6,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Bins',header=TRUE)a<-table.element(a,'Midpoint',header=TRUE)a<-table.element(a,'Abs. Frequency',header=TRUE)a<-table.element(a,'Rel. Frequency',header=TRUE)a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE)a<-table.element(a,'Density',header=TRUE)a<-table.row.end(a)crf <- 0mynumrows <- (length(myhist$breaks)-1)for (i in 1:mynumrows) {a<-table.row.start(a)dum <- paste('[',myhist$breaks[i],sep='')dum <- paste(dum,myhist$breaks[i+1],sep=',')if (i==mynumrows)dum <- paste(dum,']',sep='')elsedum <- paste(dum,'[',sep='')a<-table.element(a,dum,header=TRUE)a<-table.element(a,myhist$mids[i])a<-table.element(a,myhist$counts[i])rf <- myhist$counts[i]/par1crf <- crf + rfa<-table.element(a,round(rf,6))a<-table.element(a,round(crf,6))a<-table.element(a,round(myhist$density[i],6))a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable3.tab')