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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, 17 Dec 2016 12:08:43 +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/Dec/17/t1481973004utapkhbw3sndzcv.htm/, Retrieved Fri, 01 Nov 2024 03:33:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300691, Retrieved Fri, 01 Nov 2024 03:33:21 +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] [N90 histogram en ...] [2016-12-17 11:08:43] [63af9ed1c5670c0e3049894fd77d93e0] [Current]
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Dataseries X:
2695.92
2769.21
3048.48
3539.23
4103.69
5008
5918
6220
6150
6259
6453
6695
7163
8050




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=300691&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=300691&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300691&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
[2000,3000[250020.1428570.1428570.000143
[3000,4000[350020.1428570.2857140.000143
[4000,5000[450010.0714290.3571437.1e-05
[5000,6000[550020.1428570.50.000143
[6000,7000[650050.3571430.8571430.000357
[7000,8000[750010.0714290.9285717.1e-05
[8000,9000]850010.07142917.1e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[2000,3000[ & 2500 & 2 & 0.142857 & 0.142857 & 0.000143 \tabularnewline
[3000,4000[ & 3500 & 2 & 0.142857 & 0.285714 & 0.000143 \tabularnewline
[4000,5000[ & 4500 & 1 & 0.071429 & 0.357143 & 7.1e-05 \tabularnewline
[5000,6000[ & 5500 & 2 & 0.142857 & 0.5 & 0.000143 \tabularnewline
[6000,7000[ & 6500 & 5 & 0.357143 & 0.857143 & 0.000357 \tabularnewline
[7000,8000[ & 7500 & 1 & 0.071429 & 0.928571 & 7.1e-05 \tabularnewline
[8000,9000] & 8500 & 1 & 0.071429 & 1 & 7.1e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300691&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][2000,3000[[/C][C]2500[/C][C]2[/C][C]0.142857[/C][C]0.142857[/C][C]0.000143[/C][/ROW]
[ROW][C][3000,4000[[/C][C]3500[/C][C]2[/C][C]0.142857[/C][C]0.285714[/C][C]0.000143[/C][/ROW]
[ROW][C][4000,5000[[/C][C]4500[/C][C]1[/C][C]0.071429[/C][C]0.357143[/C][C]7.1e-05[/C][/ROW]
[ROW][C][5000,6000[[/C][C]5500[/C][C]2[/C][C]0.142857[/C][C]0.5[/C][C]0.000143[/C][/ROW]
[ROW][C][6000,7000[[/C][C]6500[/C][C]5[/C][C]0.357143[/C][C]0.857143[/C][C]0.000357[/C][/ROW]
[ROW][C][7000,8000[[/C][C]7500[/C][C]1[/C][C]0.071429[/C][C]0.928571[/C][C]7.1e-05[/C][/ROW]
[ROW][C][8000,9000][/C][C]8500[/C][C]1[/C][C]0.071429[/C][C]1[/C][C]7.1e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300691&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300691&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
[2000,3000[250020.1428570.1428570.000143
[3000,4000[350020.1428570.2857140.000143
[4000,5000[450010.0714290.3571437.1e-05
[5000,6000[550020.1428570.50.000143
[6000,7000[650050.3571430.8571430.000357
[7000,8000[750010.0714290.9285717.1e-05
[8000,9000]850010.07142917.1e-05



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 {
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')
}