Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 17 Aug 2015 09:03:50 +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/2015/Aug/17/t1439798645ufa5dg4daleoes4.htm/, Retrieved Wed, 15 May 2024 03:58:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280239, Retrieved Wed, 15 May 2024 03:58:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [omzetontwikkeling...] [2014-09-24 09:10:11] [3d50c3f1d1505d45371c80c331b9aa00]
- R  D  [Histogram] [] [2015-07-23 12:50:11] [74be16979710d4c4e7c6647856088456]
- R P       [Histogram] [] [2015-08-17 08:03:50] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
3469648.00
3456726.00
3443622.00
3416504.00
3684772.00
3670576.00
3469648.00
3336060.00
3348982.00
3348982.00
3363360.00
3389204.00
3429426.00
3429426.00
3403582.00
3336060.00
3684772.00
3737916.00
3657654.00
3469648.00
3550092.00
3429426.00
3483844.00
3509870.00
3536988.00
3469648.00
3483844.00
3389204.00
3684772.00
3778138.00
3697876.00
3550092.00
3710798.00
3536988.00
3697876.00
3684772.00
3724994.00
3577210.00
3737916.00
3724994.00
3966144.00
3911726.00
3697876.00
3590132.00
3737916.00
3536988.00
3684772.00
3710798.00
3765216.00
3644732.00
3710798.00
3751020.00
3898804.00
3778138.00
3617432.00
3443622.00
3604510.00
3162250.00
3376282.00
3496766.00
3617432.00
3443622.00
3443622.00
3443622.00
3536988.00
3403582.00
3228498.00
3081988.00
3188276.00
2773316.00
3027570.00
3175354.00
3202472.00
3054688.00
3067610.00
3027570.00
3162250.00
3067610.00
2881060.00
2746198.00
2974244.00
2479022.00
2800616.00
2947126.00
2947126.00
2773316.00
2612610.00
2599688.00
2746198.00
2612610.00
2358538.00
2183454.00
2371460.00
1929382.00
2331238.00
2545088.00
2612610.00
2464826.00
2278094.00
2411682.00
2464826.00
2424604.00
2022566.00
1836016.00
1969422.00
1567566.00
1982526.00
2130310.00
2250794.00
2049866.00
1861860.00
1969422.00
2022566.00
1916278.00
1514422.00
1339338.00
1500044.00
1057966.00
1540266.00
1836016.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280239&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280239&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280239&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1e+06,1500000[125000020.0327870.0327870
[1500000,2e+06[1750000120.1967210.2295080
[2e+06,2500000[2250000150.2459020.475410
[2500000,3e+06[2750000140.2295080.7049180
[3e+06,3500000[3250000160.2622950.9672131e-06
[3500000,4e+06]375000020.03278710

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1e+06,1500000[ & 1250000 & 2 & 0.032787 & 0.032787 & 0 \tabularnewline
[1500000,2e+06[ & 1750000 & 12 & 0.196721 & 0.229508 & 0 \tabularnewline
[2e+06,2500000[ & 2250000 & 15 & 0.245902 & 0.47541 & 0 \tabularnewline
[2500000,3e+06[ & 2750000 & 14 & 0.229508 & 0.704918 & 0 \tabularnewline
[3e+06,3500000[ & 3250000 & 16 & 0.262295 & 0.967213 & 1e-06 \tabularnewline
[3500000,4e+06] & 3750000 & 2 & 0.032787 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280239&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][1e+06,1500000[[/C][C]1250000[/C][C]2[/C][C]0.032787[/C][C]0.032787[/C][C]0[/C][/ROW]
[ROW][C][1500000,2e+06[[/C][C]1750000[/C][C]12[/C][C]0.196721[/C][C]0.229508[/C][C]0[/C][/ROW]
[ROW][C][2e+06,2500000[[/C][C]2250000[/C][C]15[/C][C]0.245902[/C][C]0.47541[/C][C]0[/C][/ROW]
[ROW][C][2500000,3e+06[[/C][C]2750000[/C][C]14[/C][C]0.229508[/C][C]0.704918[/C][C]0[/C][/ROW]
[ROW][C][3e+06,3500000[[/C][C]3250000[/C][C]16[/C][C]0.262295[/C][C]0.967213[/C][C]1e-06[/C][/ROW]
[ROW][C][3500000,4e+06][/C][C]3750000[/C][C]2[/C][C]0.032787[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280239&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280239&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
[1e+06,1500000[125000020.0327870.0327870
[1500000,2e+06[1750000120.1967210.2295080
[2e+06,2500000[2250000150.2459020.475410
[2500000,3e+06[2750000140.2295080.7049180
[3e+06,3500000[3250000160.2622950.9672131e-06
[3500000,4e+06]375000020.03278710



Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Interval/Ratio ;
Parameters (R input):
par1 = ; par2 = grey ; par3 = FALSE ; par4 = Interval/Ratio ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
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 {
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')
}