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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, 29 Nov 2016 12:21:25 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Nov/29/t1480418531edegvilf0lfpj7s.htm/, Retrieved Fri, 28 Aug 2026 18:39:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297255, Retrieved Fri, 28 Aug 2026 18:39:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact412

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Frequentietabel ] [2016-11-29 11:15:38] [5762ada4fdcbcd6b57f6a9b67541240f]
- R  D    [Histogram] [frequentietabel K...] [2016-11-29 11:21:25] [1440fd85db505f66df8a556f9c91a076] [Current]
-    D      [Histogram] [frequentietabel K...] [2016-11-29 11:24:12] [5762ada4fdcbcd6b57f6a9b67541240f]
-    D        [Histogram] [frequentietabel K...] [2016-11-29 11:26:21] [5762ada4fdcbcd6b57f6a9b67541240f]
- RMPD      [Pearson Correlation] [pearson correlati...] [2016-11-30 10:34:24] [04dacbed60646b14bd7632ed6ec4d25d]
-    D        [Pearson Correlation] [correlatie KVDD2] [2016-11-30 10:50:21] [04dacbed60646b14bd7632ed6ec4d25d]
- R  D        [Pearson Correlation] [correlatie KVDD3] [2016-11-30 10:59:18] [04dacbed60646b14bd7632ed6ec4d25d]
- R  D        [Pearson Correlation] [correlatie KVDD4] [2016-11-30 11:06:05] [04dacbed60646b14bd7632ed6ec4d25d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4
3
3
4
3
4
4
2
1
4
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Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297255&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=297255&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297255&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0.5,1.5[160.0365850.0365850.036585
[1.5,2.5[2210.1280490.1646340.128049
[2.5,3.5[3570.3475610.5121950.347561
[3.5,4.5[4700.4268290.9390240.426829
[4.5,5.5]5100.06097610.060976

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0.5,1.5[ & 1 & 6 & 0.036585 & 0.036585 & 0.036585 \tabularnewline
[1.5,2.5[ & 2 & 21 & 0.128049 & 0.164634 & 0.128049 \tabularnewline
[2.5,3.5[ & 3 & 57 & 0.347561 & 0.512195 & 0.347561 \tabularnewline
[3.5,4.5[ & 4 & 70 & 0.426829 & 0.939024 & 0.426829 \tabularnewline
[4.5,5.5] & 5 & 10 & 0.060976 & 1 & 0.060976 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297255&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][0.5,1.5[[/C][C]1[/C][C]6[/C][C]0.036585[/C][C]0.036585[/C][C]0.036585[/C][/ROW]
[ROW][C][1.5,2.5[[/C][C]2[/C][C]21[/C][C]0.128049[/C][C]0.164634[/C][C]0.128049[/C][/ROW]
[ROW][C][2.5,3.5[[/C][C]3[/C][C]57[/C][C]0.347561[/C][C]0.512195[/C][C]0.347561[/C][/ROW]
[ROW][C][3.5,4.5[[/C][C]4[/C][C]70[/C][C]0.426829[/C][C]0.939024[/C][C]0.426829[/C][/ROW]
[ROW][C][4.5,5.5][/C][C]5[/C][C]10[/C][C]0.060976[/C][C]1[/C][C]0.060976[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297255&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297255&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
[0.5,1.5[160.0365850.0365850.036585
[1.5,2.5[2210.1280490.1646340.128049
[2.5,3.5[3570.3475610.5121950.347561
[3.5,4.5[4700.4268290.9390240.426829
[4.5,5.5]5100.06097610.060976


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par2 = red ; par3 = FALSE ; par4 = 5-point Likert ;
Parameters (R input):
par1 = ; par2 = red ; par3 = FALSE ; par4 = 5-point Likert ;
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 {
barplot(mytab <- sort(table(x),T),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,'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')
}