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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSun, 03 Oct 2010 11:38:58 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/03/t1286105892xa8rcq580114btf.htm/, Retrieved Sat, 23 May 2026 23:16:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=80182, Retrieved Sat, 23 May 2026 23:16:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact400

Tree of Dependent Computations

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]
-   PD    [Histogram] [Workshop 1 - Task 3] [2010-10-03 11:38:58] [bff44ea937c3f909b1dc9a8bfab919e2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4,813
8,95
33,999
37,028
39,047
57,47
59,609
62,156
64,016
70,939
72,844
85,094
86,58
103,898
109,215
131,812
136,452
136,813
137,55
140,321
150,034
156,187
158,047
169,861
171,26
171,328
180,818
183,186
183,613
184,641
187,881
190,157
190,379
191,835
192,797
193,299
197,549
198,296
199,297
199,746
200,156
203,077
204,386
206,771
206,893
207,533
208,108
211,655
213,361
213,511
213,923
216,046
216,548
216,886
217,465
218,761
220,553
221,588
223,166
226,731
229,641
232,444
232,669
235,577
236,302
236,71
238,502
239,89
240,755
241,171
242,205
242,344
246,542
249,148
250,407
251,422
252,64
257,102
257,567
259,7
260,642
261,596
262,517
262,875
263,906
265,777
266,793
274,482
275,562
278,741
287,069
289,714
293,671
295,281
308,16
308,174
308,532
313,906
315,955
324,04
330,563
348,821
350,089
356,725
366,936
380,155
380,531
383,703
386,688
388,3
392,25
401,422
401,915
403,064
403,556
406,167
421,403
426,113
435,956
438,555
440,31
441,437
449,594
475,834
506,652
556,277
601,162
611,281
645,285
653,641
662,883
694,87
699,645
756,46

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80182&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80182&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80182&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,20[1020.0149250.0149250.000746
[20,40[3030.0223880.0373130.001119
[40,60[5020.0149250.0522390.000746
[60,80[7040.0298510.082090.001493
[80,100[9020.0149250.0970150.000746
[100,120[11020.0149250.111940.000746
[120,140[13040.0298510.1417910.001493
[140,160[15040.0298510.1716420.001493
[160,180[17030.0223880.194030.001119
[180,200[190140.1044780.2985070.005224
[200,220[210160.1194030.417910.00597
[220,240[230120.0895520.5074630.004478
[240,260[250120.0895520.5970150.004478
[260,280[270100.0746270.6716420.003731
[280,300[29040.0298510.7014930.001493
[300,320[31050.0373130.7388060.001866
[320,340[33020.0149250.7537310.000746
[340,360[35030.0223880.7761190.001119
[360,380[37010.0074630.7835820.000373
[380,400[39060.0447760.8283580.002239
[400,420[41050.0373130.8656720.001866
[420,440[43040.0298510.8955220.001493
[440,460[45030.0223880.917910.001119
[460,480[47010.0074630.9253730.000373
[480,500[490000.9253730
[500,520[51010.0074630.9328360.000373
[520,540[530000.9328360
[540,560[55010.0074630.9402990.000373
[560,580[570000.9402990
[580,600[590000.9402990
[600,620[61020.0149250.9552240.000746
[620,640[630000.9552240
[640,660[65020.0149250.9701490.000746
[660,680[67010.0074630.9776120.000373
[680,700[69020.0149250.9925370.000746
[700,720[710000.9925370
[720,740[730000.9925370
[740,760]75010.00746310.000373

\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=80182&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=80182&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80182&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,20[1020.0149250.0149250.000746
[20,40[3030.0223880.0373130.001119
[40,60[5020.0149250.0522390.000746
[60,80[7040.0298510.082090.001493
[80,100[9020.0149250.0970150.000746
[100,120[11020.0149250.111940.000746
[120,140[13040.0298510.1417910.001493
[140,160[15040.0298510.1716420.001493
[160,180[17030.0223880.194030.001119
[180,200[190140.1044780.2985070.005224
[200,220[210160.1194030.417910.00597
[220,240[230120.0895520.5074630.004478
[240,260[250120.0895520.5970150.004478
[260,280[270100.0746270.6716420.003731
[280,300[29040.0298510.7014930.001493
[300,320[31050.0373130.7388060.001866
[320,340[33020.0149250.7537310.000746
[340,360[35030.0223880.7761190.001119
[360,380[37010.0074630.7835820.000373
[380,400[39060.0447760.8283580.002239
[400,420[41050.0373130.8656720.001866
[420,440[43040.0298510.8955220.001493
[440,460[45030.0223880.917910.001119
[460,480[47010.0074630.9253730.000373
[480,500[490000.9253730
[500,520[51010.0074630.9328360.000373
[520,540[530000.9328360
[540,560[55010.0074630.9402990.000373
[560,580[570000.9402990
[580,600[590000.9402990
[600,620[61020.0149250.9552240.000746
[620,640[630000.9552240
[640,660[65020.0149250.9701490.000746
[660,680[67010.0074630.9776120.000373
[680,700[69020.0149250.9925370.000746
[700,720[710000.9925370
[720,740[730000.9925370
[740,760]75010.00746310.000373


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = HPC Retail Sales ; par2 = http://www.economagic.com ; par3 = US Retail Sales: Health and personal care stores: NAICS 446: NSA: Millions of dollars ; par4 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = grey ; par3 = FALSE ; par4 = Interval/Ratio ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
if (par3 == 'TRUE') par3 <- TRUE
if (par3 == 'FALSE') par3 <- FALSE
if (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 <- 3
if (par1 > 50) par1 <- 50
myhist<-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])) {
myhist
n <- 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 <- 0
if (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='')
else
dum <- paste(mybracket,myhist$breaks[i],sep='')
dum <- paste(dum,myhist$breaks[i+1],sep=',')
if (i==mynumrows)
dum <- paste(dum,']',sep='')
else
dum <- 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$counts[i]/n
crf <- crf + rf
a<-table.element(a,round(rf,6))
a<-table.element(a,round(crf,6))
a<-table.element(a,round(myhist$density[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
} else {
mytab
reltab <- 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')
}