## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 03 Nov 2012 11:15:41 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/03/t1351955804xp44jbazqf6u3vw.htm/, Retrieved Sat, 13 Aug 2022 21:12:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185745, Retrieved Sat, 13 Aug 2022 21:12:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Bad example of Hi...] [2010-09-25 09:28:23] [b98453cac15ba1066b407e146608df68]
- R     [Histogram] [] [2011-09-27 13:07:18] [f381152ed5e87cd86e751bfc27f55bf8]
-   P       [Histogram] [Extra histogram] [2012-11-03 15:15:41] [3335f298c0b702cf6bacf0a9219000f9] [Current]
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Dataseries X:
426.113
383.703
232.444
70.939
226.731
947.293
611.281
158.047
33.999
37.028
388.3
506.652
392.25
180.818
198.296
217.465
275.562
1030.944
57.47
136.452
556.277
213.361
274.482
220.553
236.71
260.642
2763.544
213.923
169.861
403.064
449.594
406.167
206.893
156.187
257.102
62.156
662.883
251.422
171.328
350.089
221.588
4.813
183.186
190.379
223.166
232.669
356.725
109.215
475.834
315.955
694.87
8.95
278.741
308.16
207.533
192.797
601.162
289.714
293.671
386.688
699.645
85.094
131.812
645.285
197.549
308.174
86.58
242.205
238.502
187.881
140.321
440.31
421.403
218.761
1305.923
137.55
262.517
348.821
150.034
64.016
261.596
259.7
171.26
203.077
249.148
211.655
252.64
438.555
239.89
401.915
216.886
184.641
380.155
653.641
313.906
366.936
236.302
229.641
235.577
103.898
263.906
241.171
216.548
295.281
193.299
204.386
257.567
136.813
240.755
59.609
213.511
380.531
242.344
250.407
183.613
191.835
266.793
246.542
330.563
403.556
208.108
324.04
308.532
199.297
200.156
262.875
287.069
190.157
199.746
265.777
435.956
72.844
756.46
206.771
4202.361
401.422
216.046
39.047
441.437


 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 'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185745&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185745&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185745&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 'Herman Ole Andreas Wold' @ wold.wessa.net

 Frequency Table (Histogram) Bins Midpoint Abs. Frequency Rel. Frequency Cumul. Rel. Freq. Density [0,20[ 10 2 0.014925 0.014925 0.000746 [20,40[ 30 3 0.022388 0.037313 0.001119 [40,60[ 50 2 0.014925 0.052239 0.000746 [60,80[ 70 4 0.029851 0.08209 0.001493 [80,100[ 90 2 0.014925 0.097015 0.000746 [100,120[ 110 2 0.014925 0.11194 0.000746 [120,140[ 130 4 0.029851 0.141791 0.001493 [140,160[ 150 4 0.029851 0.171642 0.001493 [160,180[ 170 3 0.022388 0.19403 0.001119 [180,200[ 190 14 0.104478 0.298507 0.005224 [200,220[ 210 16 0.119403 0.41791 0.00597 [220,240[ 230 12 0.089552 0.507463 0.004478 [240,260[ 250 12 0.089552 0.597015 0.004478 [260,280[ 270 10 0.074627 0.671642 0.003731 [280,300[ 290 4 0.029851 0.701493 0.001493 [300,320[ 310 5 0.037313 0.738806 0.001866 [320,340[ 330 2 0.014925 0.753731 0.000746 [340,360[ 350 3 0.022388 0.776119 0.001119 [360,380[ 370 1 0.007463 0.783582 0.000373 [380,400[ 390 6 0.044776 0.828358 0.002239 [400,420[ 410 5 0.037313 0.865672 0.001866 [420,440[ 430 4 0.029851 0.895522 0.001493 [440,460[ 450 3 0.022388 0.91791 0.001119 [460,480[ 470 1 0.007463 0.925373 0.000373 [480,500[ 490 0 0 0.925373 0 [500,520[ 510 1 0.007463 0.932836 0.000373 [520,540[ 530 0 0 0.932836 0 [540,560[ 550 1 0.007463 0.940299 0.000373 [560,580[ 570 0 0 0.940299 0 [580,600[ 590 0 0 0.940299 0 [600,620[ 610 2 0.014925 0.955224 0.000746 [620,640[ 630 0 0 0.955224 0 [640,660[ 650 2 0.014925 0.970149 0.000746 [660,680[ 670 1 0.007463 0.977612 0.000373 [680,700[ 690 2 0.014925 0.992537 0.000746 [700,720[ 710 0 0 0.992537 0 [720,740[ 730 0 0 0.992537 0 [740,760] 750 1 0.007463 1 0.000373

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,20[ & 10 & 2 & 0.014925 & 0.014925 & 0.000746 \tabularnewline
[20,40[ & 30 & 3 & 0.022388 & 0.037313 & 0.001119 \tabularnewline
[40,60[ & 50 & 2 & 0.014925 & 0.052239 & 0.000746 \tabularnewline
[60,80[ & 70 & 4 & 0.029851 & 0.08209 & 0.001493 \tabularnewline
[80,100[ & 90 & 2 & 0.014925 & 0.097015 & 0.000746 \tabularnewline
[100,120[ & 110 & 2 & 0.014925 & 0.11194 & 0.000746 \tabularnewline
[120,140[ & 130 & 4 & 0.029851 & 0.141791 & 0.001493 \tabularnewline
[140,160[ & 150 & 4 & 0.029851 & 0.171642 & 0.001493 \tabularnewline
[160,180[ & 170 & 3 & 0.022388 & 0.19403 & 0.001119 \tabularnewline
[180,200[ & 190 & 14 & 0.104478 & 0.298507 & 0.005224 \tabularnewline
[200,220[ & 210 & 16 & 0.119403 & 0.41791 & 0.00597 \tabularnewline
[220,240[ & 230 & 12 & 0.089552 & 0.507463 & 0.004478 \tabularnewline
[240,260[ & 250 & 12 & 0.089552 & 0.597015 & 0.004478 \tabularnewline
[260,280[ & 270 & 10 & 0.074627 & 0.671642 & 0.003731 \tabularnewline
[280,300[ & 290 & 4 & 0.029851 & 0.701493 & 0.001493 \tabularnewline
[300,320[ & 310 & 5 & 0.037313 & 0.738806 & 0.001866 \tabularnewline
[320,340[ & 330 & 2 & 0.014925 & 0.753731 & 0.000746 \tabularnewline
[340,360[ & 350 & 3 & 0.022388 & 0.776119 & 0.001119 \tabularnewline
[360,380[ & 370 & 1 & 0.007463 & 0.783582 & 0.000373 \tabularnewline
[380,400[ & 390 & 6 & 0.044776 & 0.828358 & 0.002239 \tabularnewline
[400,420[ & 410 & 5 & 0.037313 & 0.865672 & 0.001866 \tabularnewline
[420,440[ & 430 & 4 & 0.029851 & 0.895522 & 0.001493 \tabularnewline
[440,460[ & 450 & 3 & 0.022388 & 0.91791 & 0.001119 \tabularnewline
[460,480[ & 470 & 1 & 0.007463 & 0.925373 & 0.000373 \tabularnewline
[480,500[ & 490 & 0 & 0 & 0.925373 & 0 \tabularnewline
[500,520[ & 510 & 1 & 0.007463 & 0.932836 & 0.000373 \tabularnewline
[520,540[ & 530 & 0 & 0 & 0.932836 & 0 \tabularnewline
[540,560[ & 550 & 1 & 0.007463 & 0.940299 & 0.000373 \tabularnewline
[560,580[ & 570 & 0 & 0 & 0.940299 & 0 \tabularnewline
[580,600[ & 590 & 0 & 0 & 0.940299 & 0 \tabularnewline
[600,620[ & 610 & 2 & 0.014925 & 0.955224 & 0.000746 \tabularnewline
[620,640[ & 630 & 0 & 0 & 0.955224 & 0 \tabularnewline
[640,660[ & 650 & 2 & 0.014925 & 0.970149 & 0.000746 \tabularnewline
[660,680[ & 670 & 1 & 0.007463 & 0.977612 & 0.000373 \tabularnewline
[680,700[ & 690 & 2 & 0.014925 & 0.992537 & 0.000746 \tabularnewline
[700,720[ & 710 & 0 & 0 & 0.992537 & 0 \tabularnewline
[720,740[ & 730 & 0 & 0 & 0.992537 & 0 \tabularnewline
[740,760] & 750 & 1 & 0.007463 & 1 & 0.000373 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185745&T=1

[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][0,20[[/C][C]10[/C][C]2[/C][C]0.014925[/C][C]0.014925[/C][C]0.000746[/C][/ROW]
[ROW][C][20,40[[/C][C]30[/C][C]3[/C][C]0.022388[/C][C]0.037313[/C][C]0.001119[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]2[/C][C]0.014925[/C][C]0.052239[/C][C]0.000746[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]4[/C][C]0.029851[/C][C]0.08209[/C][C]0.001493[/C][/ROW]
[ROW][C][80,100[[/C][C]90[/C][C]2[/C][C]0.014925[/C][C]0.097015[/C][C]0.000746[/C][/ROW]
[ROW][C][100,120[[/C][C]110[/C][C]2[/C][C]0.014925[/C][C]0.11194[/C][C]0.000746[/C][/ROW]
[ROW][C][120,140[[/C][C]130[/C][C]4[/C][C]0.029851[/C][C]0.141791[/C][C]0.001493[/C][/ROW]
[ROW][C][140,160[[/C][C]150[/C][C]4[/C][C]0.029851[/C][C]0.171642[/C][C]0.001493[/C][/ROW]
[ROW][C][160,180[[/C][C]170[/C][C]3[/C][C]0.022388[/C][C]0.19403[/C][C]0.001119[/C][/ROW]
[ROW][C][180,200[[/C][C]190[/C][C]14[/C][C]0.104478[/C][C]0.298507[/C][C]0.005224[/C][/ROW]
[ROW][C][200,220[[/C][C]210[/C][C]16[/C][C]0.119403[/C][C]0.41791[/C][C]0.00597[/C][/ROW]
[ROW][C][220,240[[/C][C]230[/C][C]12[/C][C]0.089552[/C][C]0.507463[/C][C]0.004478[/C][/ROW]
[ROW][C][240,260[[/C][C]250[/C][C]12[/C][C]0.089552[/C][C]0.597015[/C][C]0.004478[/C][/ROW]
[ROW][C][260,280[[/C][C]270[/C][C]10[/C][C]0.074627[/C][C]0.671642[/C][C]0.003731[/C][/ROW]
[ROW][C][280,300[[/C][C]290[/C][C]4[/C][C]0.029851[/C][C]0.701493[/C][C]0.001493[/C][/ROW]
[ROW][C][300,320[[/C][C]310[/C][C]5[/C][C]0.037313[/C][C]0.738806[/C][C]0.001866[/C][/ROW]
[ROW][C][320,340[[/C][C]330[/C][C]2[/C][C]0.014925[/C][C]0.753731[/C][C]0.000746[/C][/ROW]
[ROW][C][340,360[[/C][C]350[/C][C]3[/C][C]0.022388[/C][C]0.776119[/C][C]0.001119[/C][/ROW]
[ROW][C][360,380[[/C][C]370[/C][C]1[/C][C]0.007463[/C][C]0.783582[/C][C]0.000373[/C][/ROW]
[ROW][C][380,400[[/C][C]390[/C][C]6[/C][C]0.044776[/C][C]0.828358[/C][C]0.002239[/C][/ROW]
[ROW][C][400,420[[/C][C]410[/C][C]5[/C][C]0.037313[/C][C]0.865672[/C][C]0.001866[/C][/ROW]
[ROW][C][420,440[[/C][C]430[/C][C]4[/C][C]0.029851[/C][C]0.895522[/C][C]0.001493[/C][/ROW]
[ROW][C][440,460[[/C][C]450[/C][C]3[/C][C]0.022388[/C][C]0.91791[/C][C]0.001119[/C][/ROW]
[ROW][C][460,480[[/C][C]470[/C][C]1[/C][C]0.007463[/C][C]0.925373[/C][C]0.000373[/C][/ROW]
[ROW][C][480,500[[/C][C]490[/C][C]0[/C][C]0[/C][C]0.925373[/C][C]0[/C][/ROW]
[ROW][C][500,520[[/C][C]510[/C][C]1[/C][C]0.007463[/C][C]0.932836[/C][C]0.000373[/C][/ROW]
[ROW][C][520,540[[/C][C]530[/C][C]0[/C][C]0[/C][C]0.932836[/C][C]0[/C][/ROW]
[ROW][C][540,560[[/C][C]550[/C][C]1[/C][C]0.007463[/C][C]0.940299[/C][C]0.000373[/C][/ROW]
[ROW][C][560,580[[/C][C]570[/C][C]0[/C][C]0[/C][C]0.940299[/C][C]0[/C][/ROW]
[ROW][C][580,600[[/C][C]590[/C][C]0[/C][C]0[/C][C]0.940299[/C][C]0[/C][/ROW]
[ROW][C][600,620[[/C][C]610[/C][C]2[/C][C]0.014925[/C][C]0.955224[/C][C]0.000746[/C][/ROW]
[ROW][C][620,640[[/C][C]630[/C][C]0[/C][C]0[/C][C]0.955224[/C][C]0[/C][/ROW]
[ROW][C][640,660[[/C][C]650[/C][C]2[/C][C]0.014925[/C][C]0.970149[/C][C]0.000746[/C][/ROW]
[ROW][C][660,680[[/C][C]670[/C][C]1[/C][C]0.007463[/C][C]0.977612[/C][C]0.000373[/C][/ROW]
[ROW][C][680,700[[/C][C]690[/C][C]2[/C][C]0.014925[/C][C]0.992537[/C][C]0.000746[/C][/ROW]
[ROW][C][700,720[[/C][C]710[/C][C]0[/C][C]0[/C][C]0.992537[/C][C]0[/C][/ROW]
[ROW][C][720,740[[/C][C]730[/C][C]0[/C][C]0[/C][C]0.992537[/C][C]0[/C][/ROW]
[ROW][C][740,760][/C][C]750[/C][C]1[/C][C]0.007463[/C][C]1[/C][C]0.000373[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185745&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185745&T=1

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 [0,20[ 10 2 0.014925 0.014925 0.000746 [20,40[ 30 3 0.022388 0.037313 0.001119 [40,60[ 50 2 0.014925 0.052239 0.000746 [60,80[ 70 4 0.029851 0.08209 0.001493 [80,100[ 90 2 0.014925 0.097015 0.000746 [100,120[ 110 2 0.014925 0.11194 0.000746 [120,140[ 130 4 0.029851 0.141791 0.001493 [140,160[ 150 4 0.029851 0.171642 0.001493 [160,180[ 170 3 0.022388 0.19403 0.001119 [180,200[ 190 14 0.104478 0.298507 0.005224 [200,220[ 210 16 0.119403 0.41791 0.00597 [220,240[ 230 12 0.089552 0.507463 0.004478 [240,260[ 250 12 0.089552 0.597015 0.004478 [260,280[ 270 10 0.074627 0.671642 0.003731 [280,300[ 290 4 0.029851 0.701493 0.001493 [300,320[ 310 5 0.037313 0.738806 0.001866 [320,340[ 330 2 0.014925 0.753731 0.000746 [340,360[ 350 3 0.022388 0.776119 0.001119 [360,380[ 370 1 0.007463 0.783582 0.000373 [380,400[ 390 6 0.044776 0.828358 0.002239 [400,420[ 410 5 0.037313 0.865672 0.001866 [420,440[ 430 4 0.029851 0.895522 0.001493 [440,460[ 450 3 0.022388 0.91791 0.001119 [460,480[ 470 1 0.007463 0.925373 0.000373 [480,500[ 490 0 0 0.925373 0 [500,520[ 510 1 0.007463 0.932836 0.000373 [520,540[ 530 0 0 0.932836 0 [540,560[ 550 1 0.007463 0.940299 0.000373 [560,580[ 570 0 0 0.940299 0 [580,600[ 590 0 0 0.940299 0 [600,620[ 610 2 0.014925 0.955224 0.000746 [620,640[ 630 0 0 0.955224 0 [640,660[ 650 2 0.014925 0.970149 0.000746 [660,680[ 670 1 0.007463 0.977612 0.000373 [680,700[ 690 2 0.014925 0.992537 0.000746 [700,720[ 710 0 0 0.992537 0 [720,740[ 730 0 0 0.992537 0 [740,760] 750 1 0.007463 1 0.000373

 PNG link Postscript link PDF link

Parameters (Session):
par1 = 30 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 30 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
x <- x[x<800]par1 <- as.numeric(par1)if (par3 == 'TRUE') par3 <- TRUEif (par3 == 'FALSE') par3 <- FALSEif (par4 == 'Unknown') par1 <- as.numeric(par1)if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1)if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5)if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5)if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5)if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5)if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5)if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5)if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5)if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5)bitmap(file='test1.png')if(is.numeric(x[1])) {if (is.na(par1)) {myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3)} else {if (par1 < 0) par1 <- 3if (par1 > 50) par1 <- 50myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3)}} else {plot(mytab <- table(x),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency')}dev.off()if(is.numeric(x[1])) {myhistn <- length(x)load(file='createtable')a<-table.start()a<-table.row.start(a)a<-table.element(a,hyperlink('histogram.htm','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 <- 0if (par3 == FALSE) mybracket <- '[' else mybracket <- ']'mynumrows <- (length(myhist$breaks)-1)for (i in 1:mynumrows) {a<-table.row.start(a)if (i == 1)dum <- paste('[',myhist$breaks[i],sep='')elsedum <- paste(mybracket,myhist$breaks[i],sep='')dum <- paste(dum,myhist$breaks[i+1],sep=',')if (i==mynumrows)dum <- paste(dum,']',sep='')elsedum <- paste(dum,mybracket,sep='')a<-table.element(a,dum,header=TRUE)a<-table.element(a,myhist$mids[i])a<-table.element(a,myhist$counts[i])rf <- myhist$counts[i]/ncrf <- crf + rfa<-table.element(a,round(rf,6))a<-table.element(a,round(crf,6))a<-table.element(a,round(myhist$density[i],6))a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable.tab')} else {mytabreltab <- mytab / sum(mytab)n <- length(mytab)load(file='createtable')a<-table.start()a<-table.row.start(a)a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Category',header=TRUE)a<-table.element(a,'Abs. Frequency',header=TRUE)a<-table.element(a,'Rel. Frequency',header=TRUE)a<-table.row.end(a)for (i in 1:n) {a<-table.row.start(a)a<-table.element(a,labels(mytab)\$x[i],header=TRUE)a<-table.element(a,mytab[i])a<-table.element(a,round(reltab[i],4))a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable1.tab')}