Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 09 Dec 2014 10:34:20 +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/09/t141812128974dfpegdk657dgs.htm/, Retrieved Thu, 16 May 2024 08:56:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264426, Retrieved Thu, 16 May 2024 08:56:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Numeracy Total Sc...] [2014-12-09 10:34:20] [80e094d39007183c022472d38ca26b6f] [Current]
Feedback Forum

Post a new message
Dataseries X:
0.75
0.53
0.69
0.47
0.63
0.75
0.47
0.63
0.63
0.53
0.34
0.66
0.88
0.44
0.41
0.38
0.66
0.41
0.59
0.72
0.84
0.78
0.84
0.50
0.63
0.56
0.59
0.53
0.31
0.34
0.50
0.41
0.44
0.38
0.47
0.47
0.44
0.31
0.41
0.66
0.34
0.44
0.63
0.22
0.75
0.50
0.69
0.78
0.16
0.59
0.72
0.41
0.31
0.38
0.66
0.69
0.63
0.53
0.41
0.28
0.69
0.47
0.38
0.78
0.44
0.44
0.53
0.28
0.31
0.47
0.47
0.47
0.44
0.66
0.41
0.63
0.50
0.38
0.63
0.56
0.66
0.72
0.41
0.69
0.44
0.72
0.50
0.44
0.69
0.59
0.72
0.50
0.63
0.25
0.50
0.34
0.50
0.31
0.53
0.50
0.53
0.31
0.47
0.41
0.59
0.44
0.56
0.78
0.31
0.69
0.47
0.56
0.69
0.56
0.47
0.63
0.56
0.19
0.53
0.38
0.38
0.59
0.72
0.81
0.88
0.59
0.50
0.09
0.34
0.47
0.69
0.38
0.66
0.78
0.38
0.44
0.75
0.38
0.41
0.47
0.53
0.38
0.88
0.78
0.44
0.66
0.56
0.72
0.50
0.47
0.16
0.59
0.69
0.59
0.38
0.69
0.56
0.75
0.59
0.13
0.63
0.75
0.81
0.69
0.59
0.28
0.69
0.56
0.50
0.59
0.63
0.66
0.53
0.28
0.81
0.88
0.41
0.50
0.69
0.56
0.66
0.31
0.47
0.47
0.41
0.31
0.72
0.66
0.44
0.53
0.47
0.47
0.53
0.81
0.38
0.44
0.81
0.56
0.53
0.63
0.50
0.59
0.38
0.63
0.59
0.78
0.59
0.47
0.38
0.94
0.53
0.75
0.63
0.78
0.63
0.84
0.56
0.88
0.66
0.84
0.69
0.88
0.78
0.66
0.69
0.88
0.63
0.91
0.63
0.63
0.72
0.56
0.56
0.59
0.78
0.78
0.78
0.75
0.59
0.81
0.31
0.53
0.41
0.53
0.94
0.13
0.50
0.66
0.69
0.63
0.69
0.72
0.50
0.00
0.56
0.78
0.56
0.56
0.75
0.91
0.47
0.69
0.72
0.75
0.69
0.47
0.53
0.63
0.84
0.81
0.72
0.72
0.47
0.81
0.69
0.56
0.47
0.69
0.84
0.31
0.63
0.53
0.72
0.59
0.41
0.84
0.72
0.50
0.78
0.06
0.81
0.63
0.69
0.75
0.56
0.66
0.75
0.59
0.75
0.59
0.53
0.63
0.66
0.66
0.66
0.50
0.84
0.47
0.66
0.56
0.69
0.63
0.53
0.66
0.72
0.56
0.69
0.75
0.84
0.63
0.84
0.63
0.63
0.66
0.81
0.78
0.56
0.66
0.50
0.78
0.63
0.84
0.63
0.56
0.81
0.56
0.50
0.56
0.66
0.56
0.78
0.63
0.72
0.69
0.31
0.56
0.78
0.72
0.69
0.72
0.59
0.44
0.81
0.53
0.47
0.66
0.63
0.69
0.63
0.81
0.81
0.63
0.75
0.63
0.47
0.78
0.63
0.84
0.63
0.53
0.69
0.75
0.69
0.50
0.69
0.72
0.59
0.63
0.47
0.69
0.38
0.47
0.84
0.75
0.56
0.56
0.78
0.38
0.59
0.75
0.69
0.56
0.88
0.72
0.69
0.66
0.78
0.84
0.72
0.72
0.56
0.56
0.72
0.59
0.47
0.63
0.50
0.78
0.78
0.59
0.59
0.50
0.59
0.59
0.72
0.66
0.69
0.59
0.63
0.09
0.72
0.44
0.72
0.63
0.47
0.41
0.50
0.22
0.75
0.53
0.75
0.75
0.59
0.88
0.72
0.59
0.72
0.78
0.78
0.63
0.50
0.63
0.78
0.78
0.72
0.53
0.63
0.50
0.72
0.38
0.75
0.34
0.44
0.72
0.56
0.91
0.50
0.59
0.50
0.72
0.59
0.13
0.63
0.63
0.13
0.75
0.50
0.09
0.75
0.72
0.53
0.63
0.69
0.59
0.75
0.59
0.84
0.69
0.72
0.69
0.53
0.72
0.72
0.88
0.91
0.66
0.75
0.63
0.22
0.59
0.88
0.81
0.59
0.63
0.72
0.75
0.50
0.59
0.75
0.66
0.50
0.50
0.66
0.88
0.50
0.72
0.81
0.91
0.56
0.59
0.59
0.50
0.50
0.50
0.56
0.69
0.44
0.63
0.47
0.69
0.50
0.47
0.34
0.47
0.63
0.66
0.50
0.53
0.47
0.50
0.56
0.78
0.63
0.75
0.88
0.69
0.63
0.84
0.53
0.69
0.72
0.69
0.41
0.59
0.47
0.63
0.75
0.56
0.59
0.47
0.63
0.41
0.72
0.75
0.72
0.59
0.63
0.69
0.78
0.81
0.75
0.84
0.50
0.47
0.78
0.84
0.72
0.66
0.44
0.75
0.50
0.69
0.41
0.53
0.72
0.69
0.72
0.81
0.44
0.75
0.66
0.50
0.34
0.59
0.50
0.59
0.50
0.34
0.72
0.84
0.72
0.78
0.75
0.69
0.81
0.59
0.59
0.59
0.63
0.50
0.69
0.66
0.81
0.72
0.66
0.69
0.81
0.84
0.53
0.69
0.59
0.44
0.63
0.81




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=264426&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=264426&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264426&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
[0,0.2[0.1120.0195440.0195440.09772
[0.2,0.4[0.3470.0765470.0960910.382736
[0.4,0.6[0.52370.3859930.4820851.929967
[0.6,0.8[0.72560.4169380.8990232.084691
[0.8,1]0.9620.10097710.504886

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,0.2[ & 0.1 & 12 & 0.019544 & 0.019544 & 0.09772 \tabularnewline
[0.2,0.4[ & 0.3 & 47 & 0.076547 & 0.096091 & 0.382736 \tabularnewline
[0.4,0.6[ & 0.5 & 237 & 0.385993 & 0.482085 & 1.929967 \tabularnewline
[0.6,0.8[ & 0.7 & 256 & 0.416938 & 0.899023 & 2.084691 \tabularnewline
[0.8,1] & 0.9 & 62 & 0.100977 & 1 & 0.504886 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264426&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][0,0.2[[/C][C]0.1[/C][C]12[/C][C]0.019544[/C][C]0.019544[/C][C]0.09772[/C][/ROW]
[ROW][C][0.2,0.4[[/C][C]0.3[/C][C]47[/C][C]0.076547[/C][C]0.096091[/C][C]0.382736[/C][/ROW]
[ROW][C][0.4,0.6[[/C][C]0.5[/C][C]237[/C][C]0.385993[/C][C]0.482085[/C][C]1.929967[/C][/ROW]
[ROW][C][0.6,0.8[[/C][C]0.7[/C][C]256[/C][C]0.416938[/C][C]0.899023[/C][C]2.084691[/C][/ROW]
[ROW][C][0.8,1][/C][C]0.9[/C][C]62[/C][C]0.100977[/C][C]1[/C][C]0.504886[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264426&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264426&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
[0,0.2[0.1120.0195440.0195440.09772
[0.2,0.4[0.3470.0765470.0960910.382736
[0.4,0.6[0.52370.3859930.4820851.929967
[0.6,0.8[0.72560.4169380.8990232.084691
[0.8,1]0.9620.10097710.504886



Parameters (Session):
par1 = 5 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 5 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '5'
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')
}