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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 computationSun, 05 Nov 2017 12:26:52 +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/Nov/05/t150988136405ivpsqkiq2yv24.htm/, Retrieved Sat, 18 May 2024 12:03:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308089, Retrieved Sat, 18 May 2024 12:03:04 +0000
QR Codes:

Original text written by user:overzichtelijke frequentie van de data
IsPrivate?No (this computation is public)
User-defined keywordsfrequency of population by age 0-21 years
Estimated Impact178
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Population IT Pug...] [2017-11-05 11:26:52] [3c189a0c4f7caff37e2cfca896353419] [Current]
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Dataseries X:
31262	
32834	
33441	
34643	
35880	
37066	
37524	
38013	
38412	
38677	
39417	
40827	
41075	
41305	
42401	
43193	
42938	
43055	
43555	
44164	
44357	
45309




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=308089&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=308089&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308089&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
[30000,32000[3100010.0454550.0454552.3e-05
[32000,34000[3300020.0909090.1363644.5e-05
[34000,36000[3500020.0909090.2272734.5e-05
[36000,38000[3700020.0909090.3181824.5e-05
[38000,40000[3900040.1818180.59.1e-05
[40000,42000[4100030.1363640.6363646.8e-05
[42000,44000[4300050.2272730.8636360.000114
[44000,46000]4500030.13636416.8e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[30000,32000[ & 31000 & 1 & 0.045455 & 0.045455 & 2.3e-05 \tabularnewline
[32000,34000[ & 33000 & 2 & 0.090909 & 0.136364 & 4.5e-05 \tabularnewline
[34000,36000[ & 35000 & 2 & 0.090909 & 0.227273 & 4.5e-05 \tabularnewline
[36000,38000[ & 37000 & 2 & 0.090909 & 0.318182 & 4.5e-05 \tabularnewline
[38000,40000[ & 39000 & 4 & 0.181818 & 0.5 & 9.1e-05 \tabularnewline
[40000,42000[ & 41000 & 3 & 0.136364 & 0.636364 & 6.8e-05 \tabularnewline
[42000,44000[ & 43000 & 5 & 0.227273 & 0.863636 & 0.000114 \tabularnewline
[44000,46000] & 45000 & 3 & 0.136364 & 1 & 6.8e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308089&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][30000,32000[[/C][C]31000[/C][C]1[/C][C]0.045455[/C][C]0.045455[/C][C]2.3e-05[/C][/ROW]
[ROW][C][32000,34000[[/C][C]33000[/C][C]2[/C][C]0.090909[/C][C]0.136364[/C][C]4.5e-05[/C][/ROW]
[ROW][C][34000,36000[[/C][C]35000[/C][C]2[/C][C]0.090909[/C][C]0.227273[/C][C]4.5e-05[/C][/ROW]
[ROW][C][36000,38000[[/C][C]37000[/C][C]2[/C][C]0.090909[/C][C]0.318182[/C][C]4.5e-05[/C][/ROW]
[ROW][C][38000,40000[[/C][C]39000[/C][C]4[/C][C]0.181818[/C][C]0.5[/C][C]9.1e-05[/C][/ROW]
[ROW][C][40000,42000[[/C][C]41000[/C][C]3[/C][C]0.136364[/C][C]0.636364[/C][C]6.8e-05[/C][/ROW]
[ROW][C][42000,44000[[/C][C]43000[/C][C]5[/C][C]0.227273[/C][C]0.863636[/C][C]0.000114[/C][/ROW]
[ROW][C][44000,46000][/C][C]45000[/C][C]3[/C][C]0.136364[/C][C]1[/C][C]6.8e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308089&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308089&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
[30000,32000[3100010.0454550.0454552.3e-05
[32000,34000[3300020.0909090.1363644.5e-05
[34000,36000[3500020.0909090.2272734.5e-05
[36000,38000[3700020.0909090.3181824.5e-05
[38000,40000[3900040.1818180.59.1e-05
[40000,42000[4100030.1363640.6363646.8e-05
[42000,44000[4300050.2272730.8636360.000114
[44000,46000]4500030.13636416.8e-05



Parameters (Session):
Parameters (R input):
par1 = ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
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 {
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')
}