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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 computationWed, 10 Dec 2014 15:57:00 +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/2014/Dec/10/t1418227141kzdyr8jevkegnkv.htm/, Retrieved Tue, 28 May 2024 16:25:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265446, Retrieved Tue, 28 May 2024 16:25:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [regressieanalyse ...] [2014-12-10 15:36:44] [1601e79f56036968990446024a6397e5]
- RMPD    [Histogram] [histogram] [2014-12-10 15:57:00] [e3ddd9a57cdbfec6dbe72df2938debe0] [Current]
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Dataseries X:
7.5
2.5
6.0
6.5
1.0
1.0
5.5
8.5
6.5
4.5
2.0
5.0
0.5
5.0
5.0
2.5
5.0
5.5
3.5
3.0
4.0
0.5
6.5
4.5
7.5
5.5
4.0
7.5
7.0
4.0
5.5
2.5
5.5
0.5
3.5
2.5
4.5
4.5
4.5
6.0
2.5
5.0
0.0
5.0
6.5
5.0
6.0
4.5
5.5
1.0
7.5
6.0
5.0
1.0
5.0
6.5
7.0
4.5
0.0
8.5
3.5
7.5
3.5
6.0
1.5
9.0
3.5
3.5
4.0
6.5
7.5
6.0
5.0
5.5
3.5
7.5
1.0
6.5
NA
6.5
6.5
7.0
3.5
1.5
4.0
7.5
4.5
0.0
3.5
5.5
5.0
4.5
2.5
7.5
7.0
0.0
4.5
3.0
1.5
3.5
2.5
5.5
8.0
1.0
5.0
4.5
3.0
3.0
8.0
2.5
7.0
0.0
1.0
3.5
5.5
5.5
0.5
7.5
9
9.5
8.5
7
8
10
7
8.5
9
9.5
4
6
8
5.5
9.5
7.5
7
7.5
8
7
7
6
10
2.5
9
8
6
8.5
6
9
8
8
9
5.5
5
7
5.5
9
2
8.5
9
8.5
9
7.5
10
9
7.5
6
10.5
8.5
8
10
10.5
6.5
9.5
8.5
7.5
5
8
10
7
7.5
7.5
9.5
6
10
7
3
6
7
10
7
3.5
8
10
5.5
6
6.5
6.5
8.5
4
9.5
8
8.5
5.5
7
9
8
10
8
6
8
5
9
4.5
8.5
7
9.5
8.5
7.5
7.5
5
7
8
5.5
8.5
7.5
9.5
7
8
8.5
3.5
6.5
6.5
10.5
8.5
8
10
10
9.5
9
10
7.5
4.5
4.5
0.5
6.5
4.5
5.5
5
6
4
8
10.5
8.5
6.5
8
8.5
5.5
7
5
3.5
5
9
8.5
5
9.5
3
1.5
6
0.5
6.5
7.5
4.5
8
9
7.5
8.5
7
9.5
6.5
9.5
6
8
9.5
8
8
9
5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265446&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265446&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265446&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'Gwilym Jenkins' @ jenkins.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,1[0.5110.0383280.0383280.038462
[1,2[1.5110.0383280.0766550.038462
[2,3[2.5110.0383280.1149830.038462
[3,4[3.5200.0696860.1846690.06993
[4,5[4.5240.0836240.2682930.083916
[5,6[5.5400.1393730.4076660.13986
[6,7[6.5360.1254360.5331010.125874
[7,8[7.5440.153310.6864110.153846
[8,9[8.5440.153310.8397210.153846
[9,10[9.5290.1010450.9407670.101399
[10,11]10.5160.0557490.9965160.055944

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,1[ & 0.5 & 11 & 0.038328 & 0.038328 & 0.038462 \tabularnewline
[1,2[ & 1.5 & 11 & 0.038328 & 0.076655 & 0.038462 \tabularnewline
[2,3[ & 2.5 & 11 & 0.038328 & 0.114983 & 0.038462 \tabularnewline
[3,4[ & 3.5 & 20 & 0.069686 & 0.184669 & 0.06993 \tabularnewline
[4,5[ & 4.5 & 24 & 0.083624 & 0.268293 & 0.083916 \tabularnewline
[5,6[ & 5.5 & 40 & 0.139373 & 0.407666 & 0.13986 \tabularnewline
[6,7[ & 6.5 & 36 & 0.125436 & 0.533101 & 0.125874 \tabularnewline
[7,8[ & 7.5 & 44 & 0.15331 & 0.686411 & 0.153846 \tabularnewline
[8,9[ & 8.5 & 44 & 0.15331 & 0.839721 & 0.153846 \tabularnewline
[9,10[ & 9.5 & 29 & 0.101045 & 0.940767 & 0.101399 \tabularnewline
[10,11] & 10.5 & 16 & 0.055749 & 0.996516 & 0.055944 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265446&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][0,1[[/C][C]0.5[/C][C]11[/C][C]0.038328[/C][C]0.038328[/C][C]0.038462[/C][/ROW]
[ROW][C][1,2[[/C][C]1.5[/C][C]11[/C][C]0.038328[/C][C]0.076655[/C][C]0.038462[/C][/ROW]
[ROW][C][2,3[[/C][C]2.5[/C][C]11[/C][C]0.038328[/C][C]0.114983[/C][C]0.038462[/C][/ROW]
[ROW][C][3,4[[/C][C]3.5[/C][C]20[/C][C]0.069686[/C][C]0.184669[/C][C]0.06993[/C][/ROW]
[ROW][C][4,5[[/C][C]4.5[/C][C]24[/C][C]0.083624[/C][C]0.268293[/C][C]0.083916[/C][/ROW]
[ROW][C][5,6[[/C][C]5.5[/C][C]40[/C][C]0.139373[/C][C]0.407666[/C][C]0.13986[/C][/ROW]
[ROW][C][6,7[[/C][C]6.5[/C][C]36[/C][C]0.125436[/C][C]0.533101[/C][C]0.125874[/C][/ROW]
[ROW][C][7,8[[/C][C]7.5[/C][C]44[/C][C]0.15331[/C][C]0.686411[/C][C]0.153846[/C][/ROW]
[ROW][C][8,9[[/C][C]8.5[/C][C]44[/C][C]0.15331[/C][C]0.839721[/C][C]0.153846[/C][/ROW]
[ROW][C][9,10[[/C][C]9.5[/C][C]29[/C][C]0.101045[/C][C]0.940767[/C][C]0.101399[/C][/ROW]
[ROW][C][10,11][/C][C]10.5[/C][C]16[/C][C]0.055749[/C][C]0.996516[/C][C]0.055944[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265446&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265446&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
[0,1[0.5110.0383280.0383280.038462
[1,2[1.5110.0383280.0766550.038462
[2,3[2.5110.0383280.1149830.038462
[3,4[3.5200.0696860.1846690.06993
[4,5[4.5240.0836240.2682930.083916
[5,6[5.5400.1393730.4076660.13986
[6,7[6.5360.1254360.5331010.125874
[7,8[7.5440.153310.6864110.153846
[8,9[8.5440.153310.8397210.153846
[9,10[9.5290.1010450.9407670.101399
[10,11]10.5160.0557490.9965160.055944



Parameters (Session):
par1 = 10 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 10 ; 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')
}