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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 computationThu, 07 Dec 2017 16:40:37 +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/2017/Dec/07/t1512661271hwh1hz9c5hkf8y9.htm/, Retrieved Thu, 16 May 2024 00:30:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308731, Retrieved Thu, 16 May 2024 00:30:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2017-12-07 15:40:37] [154f1e25dcfb4432ca4e5083a6df5da0] [Current]
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Dataseries X:
3
3
3
5
3
4
3
4
4
4
3
4
4
4
2
5
4
5
5
4
4
2
4
2
3
4
4
5
3
3
4
2
3
4
3
4
3
3
3
4
5
5
3
3
4
3
5
3
4
4
5
3
5
3
3
4
4
3
4
4
2
3
3
5
2
4
3
4
5
3
3
4
4
4
4
3
3
3
4
4
3
4
3
5
4
4
4
3
3
4
5
4
4
3
4
3
5
2
3
5
3
4
3
4
4
4
4
4
3
4
2
4
4
4
4
4
5
2
3
2
3
3
2
2
2
4
4
4
2
2
2
2
4
2
4
2
3
3
3
4
1
4
4
3
4
2
3
5
4
3
3
3
2
3
4
3
4
3
4
3
4
4
3
2
4
3
4
3
3
4
3
5
4
4
4
4
4
4
4
2
4
2
1
5
3
3
4
4
3
4
4
3
4
2
2
4
4
3
3
3
4
3
2
4
3
4
2
4
3
4
4
2
4
4
3
5
4
5
2
3
2
2
4
3
3
2
3
4
3
4
4
3
4
4
4
4
4
4
2
4
3
2
4
2
4
2
2
2
4
3
3
4
4
2
3
3
3
3
2
4
2
3
4
4
4
4
4
3
2
4
5
2
4
4
4
1
4
4
3
4
2
3
4
5
3
4
3
4
3
4
4
5
4
4
3
4
4
3
5
4
3
4
4
3
3
3
4
4
4
4
2
3
4
3
4
3
3
3
3
4
3
3
3
4
2
3
4
3
5
2
3
3
3
3
3
3
4
5
3
2
2
2
4
2
3
4
4
4
3
5
5
4
3
4
2
5
4
4
2
5
4
2
3
2
3
3
3
4
4
5
4
3
4
2
4
4
3
3
4
4
3
3
4
5
4
3
2
3
4
4
4
3
3
5
4
3
3
3
3
2
3
2
3
3
2
4
3
4
3
3
4
2
4
3
4
3
5
4
3
4
1
3
4
2
2
4
4
3
3
5
3
2
3
5
5
3
4
3
3
3
3
2
4
4
4
4




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308731&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]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308731&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308731&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1,1.5[1.2540.0089690.0089690.017937
[1.5,2[1.75000.0089690
[2,2.5[2.25660.1479820.1569510.295964
[2.5,3[2.75000.1569510
[3,3.5[3.251540.3452910.5022420.690583
[3.5,4[3.75000.5022420
[4,4.5[4.251830.4103140.9125560.820628
[4.5,5]4.75390.08744410.174888

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1,1.5[ & 1.25 & 4 & 0.008969 & 0.008969 & 0.017937 \tabularnewline
[1.5,2[ & 1.75 & 0 & 0 & 0.008969 & 0 \tabularnewline
[2,2.5[ & 2.25 & 66 & 0.147982 & 0.156951 & 0.295964 \tabularnewline
[2.5,3[ & 2.75 & 0 & 0 & 0.156951 & 0 \tabularnewline
[3,3.5[ & 3.25 & 154 & 0.345291 & 0.502242 & 0.690583 \tabularnewline
[3.5,4[ & 3.75 & 0 & 0 & 0.502242 & 0 \tabularnewline
[4,4.5[ & 4.25 & 183 & 0.410314 & 0.912556 & 0.820628 \tabularnewline
[4.5,5] & 4.75 & 39 & 0.087444 & 1 & 0.174888 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308731&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][1,1.5[[/C][C]1.25[/C][C]4[/C][C]0.008969[/C][C]0.008969[/C][C]0.017937[/C][/ROW]
[ROW][C][1.5,2[[/C][C]1.75[/C][C]0[/C][C]0[/C][C]0.008969[/C][C]0[/C][/ROW]
[ROW][C][2,2.5[[/C][C]2.25[/C][C]66[/C][C]0.147982[/C][C]0.156951[/C][C]0.295964[/C][/ROW]
[ROW][C][2.5,3[[/C][C]2.75[/C][C]0[/C][C]0[/C][C]0.156951[/C][C]0[/C][/ROW]
[ROW][C][3,3.5[[/C][C]3.25[/C][C]154[/C][C]0.345291[/C][C]0.502242[/C][C]0.690583[/C][/ROW]
[ROW][C][3.5,4[[/C][C]3.75[/C][C]0[/C][C]0[/C][C]0.502242[/C][C]0[/C][/ROW]
[ROW][C][4,4.5[[/C][C]4.25[/C][C]183[/C][C]0.410314[/C][C]0.912556[/C][C]0.820628[/C][/ROW]
[ROW][C][4.5,5][/C][C]4.75[/C][C]39[/C][C]0.087444[/C][C]1[/C][C]0.174888[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308731&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308731&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
[1,1.5[1.2540.0089690.0089690.017937
[1.5,2[1.75000.0089690
[2,2.5[2.25660.1479820.1569510.295964
[2.5,3[2.75000.1569510
[3,3.5[3.251540.3452910.5022420.690583
[3.5,4[3.75000.5022420
[4,4.5[4.251830.4103140.9125560.820628
[4.5,5]4.75390.08744410.174888



Parameters (Session):
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 {
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')
}