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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 computationMon, 01 Dec 2014 12:23:08 +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/01/t1417436595cyic0v6fgjiica0.htm/, Retrieved Fri, 21 Feb 2025 18:09:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261796, Retrieved Fri, 21 Feb 2025 18:09:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variability] [Pregnancy and Cog...] [2009-10-24 23:53:36] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD  [Correlation] [Cognition in Preg...] [2011-10-24 17:01:26] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD    [Histogram, QQplot and Density] [] [2014-11-27 18:05:57] [2ed850bce66a69e832a0f7b173f93b7f]
- RMPD        [Histogram] [] [2014-12-01 12:23:08] [1d69101def6b4b74d3c2b7fa04918ae6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4.8
5.4
6
6
4
6
4.2
4.2
4.2
4
4.6
5.666666667
3.8
4.8
4.2
4
5.4
4.6
4
4.4
5
5.4
5.2
4.4
4
3.4
4.4
4
4.4
4.4
4
4.8
4
4
5
4
3.4
4
5.4
4.2
4
5.6
4.8
4.4
4.6
4
5.2
4.8
4.6
4
4.2
4.6
4.4
5
5
4
3.8
5.2
4.2
4.4
4.2
6
4.8
4
4.4
4
4.8
4.8
5.6
6
4
4.2
5
4.4
4.2
4.6
4.4
4
4
4
4.2
4
5
4.2
5.4
4
6
3.8
5
4.4
5
4.4
5
4.2
4.6
5

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261796&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261796&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261796&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'Gertrude Mary Cox' @ cox.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[3,3.5[3.2520.0208330.0208330.041667
[3.5,4[3.7530.031250.0520830.0625
[4,4.5[4.25490.5104170.56251.020833
[4.5,5[4.75150.156250.718750.3125
[5,5.5[5.25180.18750.906250.375
[5.5,6]5.7590.0937510.1875

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[3,3.5[ & 3.25 & 2 & 0.020833 & 0.020833 & 0.041667 \tabularnewline
[3.5,4[ & 3.75 & 3 & 0.03125 & 0.052083 & 0.0625 \tabularnewline
[4,4.5[ & 4.25 & 49 & 0.510417 & 0.5625 & 1.020833 \tabularnewline
[4.5,5[ & 4.75 & 15 & 0.15625 & 0.71875 & 0.3125 \tabularnewline
[5,5.5[ & 5.25 & 18 & 0.1875 & 0.90625 & 0.375 \tabularnewline
[5.5,6] & 5.75 & 9 & 0.09375 & 1 & 0.1875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261796&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][3,3.5[[/C][C]3.25[/C][C]2[/C][C]0.020833[/C][C]0.020833[/C][C]0.041667[/C][/ROW]
[ROW][C][3.5,4[[/C][C]3.75[/C][C]3[/C][C]0.03125[/C][C]0.052083[/C][C]0.0625[/C][/ROW]
[ROW][C][4,4.5[[/C][C]4.25[/C][C]49[/C][C]0.510417[/C][C]0.5625[/C][C]1.020833[/C][/ROW]
[ROW][C][4.5,5[[/C][C]4.75[/C][C]15[/C][C]0.15625[/C][C]0.71875[/C][C]0.3125[/C][/ROW]
[ROW][C][5,5.5[[/C][C]5.25[/C][C]18[/C][C]0.1875[/C][C]0.90625[/C][C]0.375[/C][/ROW]
[ROW][C][5.5,6][/C][C]5.75[/C][C]9[/C][C]0.09375[/C][C]1[/C][C]0.1875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261796&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261796&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
[3,3.5[3.2520.0208330.0208330.041667
[3.5,4[3.7530.031250.0520830.0625
[4,4.5[4.25490.5104170.56251.020833
[4.5,5[4.75150.156250.718750.3125
[5,5.5[5.25180.18750.906250.375
[5.5,6]5.7590.0937510.1875


Figures (Output of Computation)

Input Parameters & R Code

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