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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 computationTue, 13 Dec 2011 15:39:48 -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/13/t1323808805nkr70x0gukeslap.htm/, Retrieved Sat, 18 Apr 2026 18:00:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154702, Retrieved Sat, 18 Apr 2026 18:00:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact355

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] [Histogram with ma...] [2010-10-04 14:39:18] [b98453cac15ba1066b407e146608df68]
- R PD    [Histogram] [Histo 5 bins doel...] [2011-12-13 20:11:14] [22f8bc702946f784836540059d0d9516]
-    D      [Histogram] [Histo 16 bins doe...] [2011-12-13 20:27:52] [22f8bc702946f784836540059d0d9516]
-    D          [Histogram] [Histo 15 bins doe...] [2011-12-13 20:39:48] [76a85a4cc6ea7903d92a0f5b9d2872d3] [Current]
-                 [Histogram] [Histo 3 bins doel...] [2011-12-13 20:40:38] [22f8bc702946f784836540059d0d9516]
-    D            [Histogram] [Histo 15 bins doe...] [2011-12-13 20:49:47] [22f8bc702946f784836540059d0d9516]
-                   [Histogram] [Histo 3 bins doel...] [2011-12-13 20:50:34] [22f8bc702946f784836540059d0d9516]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6
0
1
2
8
3
2
6
5
2
3
3
7
10
3
4
5
4
4
4
7
2
1
1
3
7
9
8
1
2
4
8
2
1
3
0
7
0
2
6
0
3
4
4
2
1
3
5
6
5
12
3
4
2
4
1
4
0
0
11
5
3
5
15
2
1
5
9
6
3

Tables (Output of Computation)





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=154702&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=154702&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154702&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,1[0.560.0857140.0857140.085714
[1,2[1.580.1142860.20.114286
[2,3[2.5100.1428570.3428570.142857
[3,4[3.5110.1571430.50.157143
[4,5[4.5100.1428570.6428570.142857
[5,6[5.570.10.7428570.1
[6,7[6.550.0714290.8142860.071429
[7,8[7.540.0571430.8714290.057143
[8,9[8.530.0428570.9142860.042857
[9,10[9.520.0285710.9428570.028571
[10,11[10.510.0142860.9571430.014286
[11,12[11.510.0142860.9714290.014286
[12,13[12.510.0142860.9857140.014286
[13,14[13.5000.9857140
[14,15]14.510.01428610.014286

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,1[ & 0.5 & 6 & 0.085714 & 0.085714 & 0.085714 \tabularnewline
[1,2[ & 1.5 & 8 & 0.114286 & 0.2 & 0.114286 \tabularnewline
[2,3[ & 2.5 & 10 & 0.142857 & 0.342857 & 0.142857 \tabularnewline
[3,4[ & 3.5 & 11 & 0.157143 & 0.5 & 0.157143 \tabularnewline
[4,5[ & 4.5 & 10 & 0.142857 & 0.642857 & 0.142857 \tabularnewline
[5,6[ & 5.5 & 7 & 0.1 & 0.742857 & 0.1 \tabularnewline
[6,7[ & 6.5 & 5 & 0.071429 & 0.814286 & 0.071429 \tabularnewline
[7,8[ & 7.5 & 4 & 0.057143 & 0.871429 & 0.057143 \tabularnewline
[8,9[ & 8.5 & 3 & 0.042857 & 0.914286 & 0.042857 \tabularnewline
[9,10[ & 9.5 & 2 & 0.028571 & 0.942857 & 0.028571 \tabularnewline
[10,11[ & 10.5 & 1 & 0.014286 & 0.957143 & 0.014286 \tabularnewline
[11,12[ & 11.5 & 1 & 0.014286 & 0.971429 & 0.014286 \tabularnewline
[12,13[ & 12.5 & 1 & 0.014286 & 0.985714 & 0.014286 \tabularnewline
[13,14[ & 13.5 & 0 & 0 & 0.985714 & 0 \tabularnewline
[14,15] & 14.5 & 1 & 0.014286 & 1 & 0.014286 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154702&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]6[/C][C]0.085714[/C][C]0.085714[/C][C]0.085714[/C][/ROW]
[ROW][C][1,2[[/C][C]1.5[/C][C]8[/C][C]0.114286[/C][C]0.2[/C][C]0.114286[/C][/ROW]
[ROW][C][2,3[[/C][C]2.5[/C][C]10[/C][C]0.142857[/C][C]0.342857[/C][C]0.142857[/C][/ROW]
[ROW][C][3,4[[/C][C]3.5[/C][C]11[/C][C]0.157143[/C][C]0.5[/C][C]0.157143[/C][/ROW]
[ROW][C][4,5[[/C][C]4.5[/C][C]10[/C][C]0.142857[/C][C]0.642857[/C][C]0.142857[/C][/ROW]
[ROW][C][5,6[[/C][C]5.5[/C][C]7[/C][C]0.1[/C][C]0.742857[/C][C]0.1[/C][/ROW]
[ROW][C][6,7[[/C][C]6.5[/C][C]5[/C][C]0.071429[/C][C]0.814286[/C][C]0.071429[/C][/ROW]
[ROW][C][7,8[[/C][C]7.5[/C][C]4[/C][C]0.057143[/C][C]0.871429[/C][C]0.057143[/C][/ROW]
[ROW][C][8,9[[/C][C]8.5[/C][C]3[/C][C]0.042857[/C][C]0.914286[/C][C]0.042857[/C][/ROW]
[ROW][C][9,10[[/C][C]9.5[/C][C]2[/C][C]0.028571[/C][C]0.942857[/C][C]0.028571[/C][/ROW]
[ROW][C][10,11[[/C][C]10.5[/C][C]1[/C][C]0.014286[/C][C]0.957143[/C][C]0.014286[/C][/ROW]
[ROW][C][11,12[[/C][C]11.5[/C][C]1[/C][C]0.014286[/C][C]0.971429[/C][C]0.014286[/C][/ROW]
[ROW][C][12,13[[/C][C]12.5[/C][C]1[/C][C]0.014286[/C][C]0.985714[/C][C]0.014286[/C][/ROW]
[ROW][C][13,14[[/C][C]13.5[/C][C]0[/C][C]0[/C][C]0.985714[/C][C]0[/C][/ROW]
[ROW][C][14,15][/C][C]14.5[/C][C]1[/C][C]0.014286[/C][C]1[/C][C]0.014286[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154702&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154702&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
[0,1[0.560.0857140.0857140.085714
[1,2[1.580.1142860.20.114286
[2,3[2.5100.1428570.3428570.142857
[3,4[3.5110.1571430.50.157143
[4,5[4.5100.1428570.6428570.142857
[5,6[5.570.10.7428570.1
[6,7[6.550.0714290.8142860.071429
[7,8[7.540.0571430.8714290.057143
[8,9[8.530.0428570.9142860.042857
[9,10[9.520.0285710.9428570.028571
[10,11[10.510.0142860.9571430.014286
[11,12[11.510.0142860.9714290.014286
[12,13[12.510.0142860.9857140.014286
[13,14[13.5000.9857140
[14,15]14.510.01428610.014286


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 15 ; 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')
}