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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 07 Aug 2017 15:34:51 +0200
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/Aug/07/t1502112905n5drip3d9jvdlxu.htm/, Retrieved Sat, 11 May 2024 21:38:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306985, Retrieved Sat, 11 May 2024 21:38:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2017-08-07 13:34:51] [bb1ebaef39f3ee233240b5c77a617fca] [Current]
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Dataseries X:
6195800,00
6172725,00
6149325,00
6100900,00
6579950,00
6554600,00
6195800,00
5957250,00
5980325,00
5980325,00
6006000,00
6052150,00
6123975,00
6123975,00
6077825,00
5957250,00
6579950,00
6674850,00
6531525,00
6195800,00
6339450,00
6123975,00
6221150,00
6267625,00
6316050,00
6195800,00
6221150,00
6052150,00
6579950,00
6746675,00
6603350,00
6339450,00
6626425,00
6316050,00
6603350,00
6579950,00
6651775,00
6387875,00
6674850,00
6651775,00
7082400,00
6985225,00
6603350,00
6410950,00
6674850,00
6316050,00
6579950,00
6626425,00
6723600,00
6508450,00
6626425,00
6698250,00
6962150,00
6746675,00
6459700,00
6149325,00
6436625,00
5646875,00
6029075,00
6244225,00
6459700,00
6149325,00
6149325,00
6149325,00
6316050,00
6077825,00
5765175,00
5503550,00
5693350,00
4952350,00
5406375,00
5670275,00
5718700,00
5454800,00
5477875,00
5406375,00
5646875,00
5477875,00
5144750,00
4903925,00
5311150,00
4426825,00
5001100,00
5262725,00
5262725,00
4952350,00
4665375,00
4642300,00
4903925,00
4665375,00
4211675,00
3899025,00
4234750,00
3445325,00
4162925,00
4544800,00
4665375,00
4401475,00
4068025,00
4306575,00
4401475,00
4329650,00
3611725,00
3278600,00
3516825,00
2799225,00
3540225,00
3804125,00
4019275,00
3660475,00
3324750,00
3516825,00
3611725,00
3421925,00
2704325,00
2391675,00
2678650,00
1889225,00
2750475,00
3278600,00




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=306985&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=306985&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306985&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
[1500000,2000000[175000010.0083330.0083330
[2000000,2500000[225000010.0083330.0166670
[2500000,3000000[275000040.0333330.050
[3000000,3500000[325000050.0416670.0916670
[3500000,4000000[375000080.0666670.1583330
[4000000,4500000[4250000100.0833330.2416670
[4500000,5000000[475000090.0750.3166670
[5000000,5500000[5250000100.0833330.40
[5500000,6000000[5750000110.0916670.4916670
[6000000,6500000[6250000350.2916670.7833331e-06
[6500000,7000000[6750000250.2083330.9916670
[7000000,7500000]725000010.00833310

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1500000,2000000[ & 1750000 & 1 & 0.008333 & 0.008333 & 0 \tabularnewline
[2000000,2500000[ & 2250000 & 1 & 0.008333 & 0.016667 & 0 \tabularnewline
[2500000,3000000[ & 2750000 & 4 & 0.033333 & 0.05 & 0 \tabularnewline
[3000000,3500000[ & 3250000 & 5 & 0.041667 & 0.091667 & 0 \tabularnewline
[3500000,4000000[ & 3750000 & 8 & 0.066667 & 0.158333 & 0 \tabularnewline
[4000000,4500000[ & 4250000 & 10 & 0.083333 & 0.241667 & 0 \tabularnewline
[4500000,5000000[ & 4750000 & 9 & 0.075 & 0.316667 & 0 \tabularnewline
[5000000,5500000[ & 5250000 & 10 & 0.083333 & 0.4 & 0 \tabularnewline
[5500000,6000000[ & 5750000 & 11 & 0.091667 & 0.491667 & 0 \tabularnewline
[6000000,6500000[ & 6250000 & 35 & 0.291667 & 0.783333 & 1e-06 \tabularnewline
[6500000,7000000[ & 6750000 & 25 & 0.208333 & 0.991667 & 0 \tabularnewline
[7000000,7500000] & 7250000 & 1 & 0.008333 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306985&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][1500000,2000000[[/C][C]1750000[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]0[/C][/ROW]
[ROW][C][2000000,2500000[[/C][C]2250000[/C][C]1[/C][C]0.008333[/C][C]0.016667[/C][C]0[/C][/ROW]
[ROW][C][2500000,3000000[[/C][C]2750000[/C][C]4[/C][C]0.033333[/C][C]0.05[/C][C]0[/C][/ROW]
[ROW][C][3000000,3500000[[/C][C]3250000[/C][C]5[/C][C]0.041667[/C][C]0.091667[/C][C]0[/C][/ROW]
[ROW][C][3500000,4000000[[/C][C]3750000[/C][C]8[/C][C]0.066667[/C][C]0.158333[/C][C]0[/C][/ROW]
[ROW][C][4000000,4500000[[/C][C]4250000[/C][C]10[/C][C]0.083333[/C][C]0.241667[/C][C]0[/C][/ROW]
[ROW][C][4500000,5000000[[/C][C]4750000[/C][C]9[/C][C]0.075[/C][C]0.316667[/C][C]0[/C][/ROW]
[ROW][C][5000000,5500000[[/C][C]5250000[/C][C]10[/C][C]0.083333[/C][C]0.4[/C][C]0[/C][/ROW]
[ROW][C][5500000,6000000[[/C][C]5750000[/C][C]11[/C][C]0.091667[/C][C]0.491667[/C][C]0[/C][/ROW]
[ROW][C][6000000,6500000[[/C][C]6250000[/C][C]35[/C][C]0.291667[/C][C]0.783333[/C][C]1e-06[/C][/ROW]
[ROW][C][6500000,7000000[[/C][C]6750000[/C][C]25[/C][C]0.208333[/C][C]0.991667[/C][C]0[/C][/ROW]
[ROW][C][7000000,7500000][/C][C]7250000[/C][C]1[/C][C]0.008333[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306985&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306985&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
[1500000,2000000[175000010.0083330.0083330
[2000000,2500000[225000010.0083330.0166670
[2500000,3000000[275000040.0333330.050
[3000000,3500000[325000050.0416670.0916670
[3500000,4000000[375000080.0666670.1583330
[4000000,4500000[4250000100.0833330.2416670
[4500000,5000000[475000090.0750.3166670
[5000000,5500000[5250000100.0833330.40
[5500000,6000000[5750000110.0916670.4916670
[6000000,6500000[6250000350.2916670.7833331e-06
[6500000,7000000[6750000250.2083330.9916670
[7000000,7500000]725000010.00833310



Parameters (Session):
Parameters (R input):
par1 = 12 ; 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')
}