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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 computationSat, 09 Dec 2017 16:51:21 +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/09/t1512835591h154rpo2tvqns1k.htm/, Retrieved Wed, 15 May 2024 00:02:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308876, Retrieved Wed, 15 May 2024 00:02:03 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [frequentie tabel] [2017-12-09 15:51:21] [257418b76be273634a64f762d7e0e083] [Current]
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Dataseries X:
7
8
8
10
8
9
8
10
7
10
8
8
6
7
9
9
8
8
10
7
7
7
6
9
7
8
10
9
8
8
10
8
4
6
7
7
3
8
8
6
10
8
4
8
7
6
9
10
9
7
10
7
10
9
7
10
8
8
6
9
7
8
8
9
5
9
6
8
10
7
5
4
9
10
8
6
6
9
3
7
9
7
8
9
9
8
9
6
7
8
7
9
9
5
6
8
10
5
8
8
10
7
9
8
8
10
9
9
6
8
5
3
6
6
10
9
9
5
6
7
8
9
3
5
5
9
10
7
8
6
5
8
7
5
6
10
10
6
4
8
5
7
10
8
7
2
7
9
8
5
8
6
7
10
8
10
9
8
10
4
6
9
4
6
7
9
8
6
4
8
8
9
6
5
5
8
8
9
7
9
8
6
7
8
8
7
7
8
8
9
9
9
8
2
8
8
8
7
10
8
10
5
4
10
8
7
5
7
9
8
8
2
9
8
5
7
8
7
5
10
6
6
5
7
8
8
4
9
4
10
6
6
8
8
8
8
8
8
7
7
8
10
10
3
8
2
4
4
9
10
6
10
10
3
9
9
6
5
4
4
6
6
8
8
5
7
6
10
8
8
9
5
10
8
9
8
7
10
10
9
4
4
8
9
10
8
5
10
8
7
8
8
9
8
6
8
8
5
9
8
8
8
6
6
9
8
9
10
8
8
7
7
10
8
7
10
7
7
9
9
8
6
8
9
2
6
8
8
7
8
6
10
10
10
8
8
7
10
5
3
2
3
4
2
6
8
8
5
10
9
8
9
8
5
7
9
8
4
7
8
7
7
9
6
7
4
6
10
9
10
8
4
8
5
8
9
8
4
8
10
6
7
10
9
8
3
8
7
7
8
8
7
7
9
9
9
4
6
6
6
8
3
8
8
6
10
2
9
6
6
5
4
7
5
8
6
9
6
4
7
2
8
9
6
5
7
8
4
9
9
9
7
5
7
9
8
6
9
8
7
7
7
8
10
6
6




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=308876&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=308876&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308876&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[2,3]2.5190.0426010.0426010.042601
]3,4]3.5250.0560540.0986550.056054
]4,5]4.5320.0717490.1704040.071749
]5,6]5.5550.1233180.2937220.123318
]6,7]6.5680.1524660.4461880.152466
]7,8]7.51220.2735430.7197310.273543
]8,9]8.5710.1591930.8789240.159193
]9,10]9.5540.12107610.121076

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[2,3] & 2.5 & 19 & 0.042601 & 0.042601 & 0.042601 \tabularnewline
]3,4] & 3.5 & 25 & 0.056054 & 0.098655 & 0.056054 \tabularnewline
]4,5] & 4.5 & 32 & 0.071749 & 0.170404 & 0.071749 \tabularnewline
]5,6] & 5.5 & 55 & 0.123318 & 0.293722 & 0.123318 \tabularnewline
]6,7] & 6.5 & 68 & 0.152466 & 0.446188 & 0.152466 \tabularnewline
]7,8] & 7.5 & 122 & 0.273543 & 0.719731 & 0.273543 \tabularnewline
]8,9] & 8.5 & 71 & 0.159193 & 0.878924 & 0.159193 \tabularnewline
]9,10] & 9.5 & 54 & 0.121076 & 1 & 0.121076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308876&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][2,3][/C][C]2.5[/C][C]19[/C][C]0.042601[/C][C]0.042601[/C][C]0.042601[/C][/ROW]
[ROW][C]]3,4][/C][C]3.5[/C][C]25[/C][C]0.056054[/C][C]0.098655[/C][C]0.056054[/C][/ROW]
[ROW][C]]4,5][/C][C]4.5[/C][C]32[/C][C]0.071749[/C][C]0.170404[/C][C]0.071749[/C][/ROW]
[ROW][C]]5,6][/C][C]5.5[/C][C]55[/C][C]0.123318[/C][C]0.293722[/C][C]0.123318[/C][/ROW]
[ROW][C]]6,7][/C][C]6.5[/C][C]68[/C][C]0.152466[/C][C]0.446188[/C][C]0.152466[/C][/ROW]
[ROW][C]]7,8][/C][C]7.5[/C][C]122[/C][C]0.273543[/C][C]0.719731[/C][C]0.273543[/C][/ROW]
[ROW][C]]8,9][/C][C]8.5[/C][C]71[/C][C]0.159193[/C][C]0.878924[/C][C]0.159193[/C][/ROW]
[ROW][C]]9,10][/C][C]9.5[/C][C]54[/C][C]0.121076[/C][C]1[/C][C]0.121076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308876&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308876&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
[2,3]2.5190.0426010.0426010.042601
]3,4]3.5250.0560540.0986550.056054
]4,5]4.5320.0717490.1704040.071749
]5,6]5.5550.1233180.2937220.123318
]6,7]6.5680.1524660.4461880.152466
]7,8]7.51220.2735430.7197310.273543
]8,9]8.5710.1591930.8789240.159193
]9,10]9.5540.12107610.121076



Parameters (Session):
par1 = 10 ; par2 = blue ; par3 = TRUE ; par4 = Unknown ;
Parameters (R input):
par1 = ; par2 = yellow ; par3 = TRUE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'yellow'
par1 <- ''
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')
}