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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 16 Dec 2011 11:12:11 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/16/t1324051964bh4i75asxj3p5tv.htm/, Retrieved Sun, 05 May 2024 15:58:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156073, Retrieved Sun, 05 May 2024 15:58:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
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 P   [Histogram] [workshop 1 -taak 3] [2011-09-30 10:58:09] [b1eb71d4db1ceb5d347df987feb4a25e]
-   PD      [Histogram] [Paper kwantitatie...] [2011-12-16 16:12:11] [3e388c05c22237d436c48535c44f60bb] [Current]
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Dataseries X:
30
28
38
30
22
26
25
18
11
26
25
38
44
30
40
34
47
30
31
23
36
36
30
25
39
34
31
31
33
25
33
35
42
43
30
33
13
32
36
0
28
14
17
32
30
35
20
28
28
39
34
26
39
39
33
28
4
39
18
14
29
44
21
16
28
35
28
38
23
36
32
29
25
27
36
28
23
40
23
40
28
34
33
28
34
30
33
22
38
26
35
8
24
29
20
29
45
37
33
33
25
32
29
28
28
31
52
21
24
41
33
32
19
20
31
31
32
18
23
17
20
12
17
30
31
10
13
22
42
1
9
32
11
25
36
31
0
24
13
8
13
19
18
33
40
22
38
24
8
35
43
43
14
41
38
45
31
13
28
31
40
30
16
37
30
35
32
27
20
18
31
31
21
39
41
13
32
18
39
14
7
17
0
30
37
0
5
1
16
32
24
17
11
24
22
12
19
13
17
15
16
24
15
17
18
20
16
16
18
22
8
17
18
16
23
22
13
13
16
16
20
22
17
18
17
12
7
17
14
23
17
14
15
17
21
18
18
17
17
16
15
21
16
14
15
17
15
15
10
6
22
21
1
18
17
4
10
16
16
9
16
17
7
15
14
14
18
12
16
21
19
16
1
16
10
19
12
2
14
17
19
14
11
4
16
20
12
15
16




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156073&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156073&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156073&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,2[180.0276820.0276820.013841
[2,4[310.003460.0311420.00173
[4,6[540.0138410.0449830.00692
[6,8[740.0138410.0588240.00692
[8,10[960.0207610.0795850.010381
[10,12[1180.0276820.1072660.013841
[12,14[13150.0519030.159170.025952
[14,16[15200.0692040.2283740.034602
[16,18[17380.1314880.3598620.065744
[18,20[19200.0692040.4290660.034602
[20,22[21150.0519030.4809690.025952
[22,24[23160.0553630.5363320.027682
[24,26[25140.0484430.5847750.024221
[26,28[2760.0207610.6055360.010381
[28,30[29180.0622840.667820.031142
[30,32[31240.0830450.7508650.041522
[32,34[33200.0692040.8200690.034602
[34,36[35110.0380620.8581310.019031
[36,38[3790.0311420.8892730.015571
[38,40[39130.0449830.9342560.022491
[40,42[4180.0276820.9619380.013841
[42,44[4350.0173010.9792390.008651
[44,46[4540.0138410.993080.00692
[46,48[4710.003460.996540.00173
[48,50[49000.996540
[50,52]5110.0034610.00173

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,2[ & 1 & 8 & 0.027682 & 0.027682 & 0.013841 \tabularnewline
[2,4[ & 3 & 1 & 0.00346 & 0.031142 & 0.00173 \tabularnewline
[4,6[ & 5 & 4 & 0.013841 & 0.044983 & 0.00692 \tabularnewline
[6,8[ & 7 & 4 & 0.013841 & 0.058824 & 0.00692 \tabularnewline
[8,10[ & 9 & 6 & 0.020761 & 0.079585 & 0.010381 \tabularnewline
[10,12[ & 11 & 8 & 0.027682 & 0.107266 & 0.013841 \tabularnewline
[12,14[ & 13 & 15 & 0.051903 & 0.15917 & 0.025952 \tabularnewline
[14,16[ & 15 & 20 & 0.069204 & 0.228374 & 0.034602 \tabularnewline
[16,18[ & 17 & 38 & 0.131488 & 0.359862 & 0.065744 \tabularnewline
[18,20[ & 19 & 20 & 0.069204 & 0.429066 & 0.034602 \tabularnewline
[20,22[ & 21 & 15 & 0.051903 & 0.480969 & 0.025952 \tabularnewline
[22,24[ & 23 & 16 & 0.055363 & 0.536332 & 0.027682 \tabularnewline
[24,26[ & 25 & 14 & 0.048443 & 0.584775 & 0.024221 \tabularnewline
[26,28[ & 27 & 6 & 0.020761 & 0.605536 & 0.010381 \tabularnewline
[28,30[ & 29 & 18 & 0.062284 & 0.66782 & 0.031142 \tabularnewline
[30,32[ & 31 & 24 & 0.083045 & 0.750865 & 0.041522 \tabularnewline
[32,34[ & 33 & 20 & 0.069204 & 0.820069 & 0.034602 \tabularnewline
[34,36[ & 35 & 11 & 0.038062 & 0.858131 & 0.019031 \tabularnewline
[36,38[ & 37 & 9 & 0.031142 & 0.889273 & 0.015571 \tabularnewline
[38,40[ & 39 & 13 & 0.044983 & 0.934256 & 0.022491 \tabularnewline
[40,42[ & 41 & 8 & 0.027682 & 0.961938 & 0.013841 \tabularnewline
[42,44[ & 43 & 5 & 0.017301 & 0.979239 & 0.008651 \tabularnewline
[44,46[ & 45 & 4 & 0.013841 & 0.99308 & 0.00692 \tabularnewline
[46,48[ & 47 & 1 & 0.00346 & 0.99654 & 0.00173 \tabularnewline
[48,50[ & 49 & 0 & 0 & 0.99654 & 0 \tabularnewline
[50,52] & 51 & 1 & 0.00346 & 1 & 0.00173 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156073&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][0,2[[/C][C]1[/C][C]8[/C][C]0.027682[/C][C]0.027682[/C][C]0.013841[/C][/ROW]
[ROW][C][2,4[[/C][C]3[/C][C]1[/C][C]0.00346[/C][C]0.031142[/C][C]0.00173[/C][/ROW]
[ROW][C][4,6[[/C][C]5[/C][C]4[/C][C]0.013841[/C][C]0.044983[/C][C]0.00692[/C][/ROW]
[ROW][C][6,8[[/C][C]7[/C][C]4[/C][C]0.013841[/C][C]0.058824[/C][C]0.00692[/C][/ROW]
[ROW][C][8,10[[/C][C]9[/C][C]6[/C][C]0.020761[/C][C]0.079585[/C][C]0.010381[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]8[/C][C]0.027682[/C][C]0.107266[/C][C]0.013841[/C][/ROW]
[ROW][C][12,14[[/C][C]13[/C][C]15[/C][C]0.051903[/C][C]0.15917[/C][C]0.025952[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]20[/C][C]0.069204[/C][C]0.228374[/C][C]0.034602[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]38[/C][C]0.131488[/C][C]0.359862[/C][C]0.065744[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]20[/C][C]0.069204[/C][C]0.429066[/C][C]0.034602[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]15[/C][C]0.051903[/C][C]0.480969[/C][C]0.025952[/C][/ROW]
[ROW][C][22,24[[/C][C]23[/C][C]16[/C][C]0.055363[/C][C]0.536332[/C][C]0.027682[/C][/ROW]
[ROW][C][24,26[[/C][C]25[/C][C]14[/C][C]0.048443[/C][C]0.584775[/C][C]0.024221[/C][/ROW]
[ROW][C][26,28[[/C][C]27[/C][C]6[/C][C]0.020761[/C][C]0.605536[/C][C]0.010381[/C][/ROW]
[ROW][C][28,30[[/C][C]29[/C][C]18[/C][C]0.062284[/C][C]0.66782[/C][C]0.031142[/C][/ROW]
[ROW][C][30,32[[/C][C]31[/C][C]24[/C][C]0.083045[/C][C]0.750865[/C][C]0.041522[/C][/ROW]
[ROW][C][32,34[[/C][C]33[/C][C]20[/C][C]0.069204[/C][C]0.820069[/C][C]0.034602[/C][/ROW]
[ROW][C][34,36[[/C][C]35[/C][C]11[/C][C]0.038062[/C][C]0.858131[/C][C]0.019031[/C][/ROW]
[ROW][C][36,38[[/C][C]37[/C][C]9[/C][C]0.031142[/C][C]0.889273[/C][C]0.015571[/C][/ROW]
[ROW][C][38,40[[/C][C]39[/C][C]13[/C][C]0.044983[/C][C]0.934256[/C][C]0.022491[/C][/ROW]
[ROW][C][40,42[[/C][C]41[/C][C]8[/C][C]0.027682[/C][C]0.961938[/C][C]0.013841[/C][/ROW]
[ROW][C][42,44[[/C][C]43[/C][C]5[/C][C]0.017301[/C][C]0.979239[/C][C]0.008651[/C][/ROW]
[ROW][C][44,46[[/C][C]45[/C][C]4[/C][C]0.013841[/C][C]0.99308[/C][C]0.00692[/C][/ROW]
[ROW][C][46,48[[/C][C]47[/C][C]1[/C][C]0.00346[/C][C]0.99654[/C][C]0.00173[/C][/ROW]
[ROW][C][48,50[[/C][C]49[/C][C]0[/C][C]0[/C][C]0.99654[/C][C]0[/C][/ROW]
[ROW][C][50,52][/C][C]51[/C][C]1[/C][C]0.00346[/C][C]1[/C][C]0.00173[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156073&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156073&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)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,2[180.0276820.0276820.013841
[2,4[310.003460.0311420.00173
[4,6[540.0138410.0449830.00692
[6,8[740.0138410.0588240.00692
[8,10[960.0207610.0795850.010381
[10,12[1180.0276820.1072660.013841
[12,14[13150.0519030.159170.025952
[14,16[15200.0692040.2283740.034602
[16,18[17380.1314880.3598620.065744
[18,20[19200.0692040.4290660.034602
[20,22[21150.0519030.4809690.025952
[22,24[23160.0553630.5363320.027682
[24,26[25140.0484430.5847750.024221
[26,28[2760.0207610.6055360.010381
[28,30[29180.0622840.667820.031142
[30,32[31240.0830450.7508650.041522
[32,34[33200.0692040.8200690.034602
[34,36[35110.0380620.8581310.019031
[36,38[3790.0311420.8892730.015571
[38,40[39130.0449830.9342560.022491
[40,42[4180.0276820.9619380.013841
[42,44[4350.0173010.9792390.008651
[44,46[4540.0138410.993080.00692
[46,48[4710.003460.996540.00173
[48,50[49000.996540
[50,52]5110.0034610.00173



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):
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')
}