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Description of Statistical Computation

Author's title

België, Werkloosheid (niet werkende werkzoekenden), brutogegevens in duize...

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 14 Feb 2011 18:49:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Feb/14/t1297710461aynyi5x70wa2chg.htm/, Retrieved Tue, 30 Apr 2024 07:20:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=118245, Retrieved Tue, 30 Apr 2024 07:20:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W1
Estimated Impact244

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [België, Werkloos...] [2011-02-14 18:49:06] [27bda1a3a981631f705f83c894f67697] [Current]
- R       [Histogram] [Werkloosheid in B...] [2011-02-22 14:39:30] [7752bb3d4bd1d160138dfe83c3ebc5bb]
- R P     [Histogram] [Werkloosheid in B...] [2011-02-22 14:46:08] [7752bb3d4bd1d160138dfe83c3ebc5bb]
- R P     [Histogram] [Werkloosheid in B...] [2011-02-22 14:48:32] [7752bb3d4bd1d160138dfe83c3ebc5bb]
- RMP     [Kernel Density Estimation] [Werkloosheid in B...] [2011-02-22 14:53:29] [7752bb3d4bd1d160138dfe83c3ebc5bb]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
476
475
470
461
455
456
517
525
523
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
577
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536
537
524
536
587
597
581
564
558
575
580
575
563
552
537
545
601
604
586
564
549
551
556

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=118245&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=118245&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=118245&T=0

As an alternative you can also use a QR Code:  
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 time0 seconds
R Server'Gwilym Jenkins' @ www.wessa.org






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[440,460[45020.0183490.0183490.000917
[460,480[47060.0550460.0733940.002752
[480,500[49030.0275230.1009170.001376
[500,520[510190.1743120.2752290.008716
[520,540[530150.1376150.4128440.006881
[540,560[550140.128440.5412840.006422
[560,580[570200.1834860.7247710.009174
[580,600[590180.1651380.8899080.008257
[600,620[61060.0550460.9449540.002752
[620,640]63060.05504610.002752

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[440,460[ & 450 & 2 & 0.018349 & 0.018349 & 0.000917 \tabularnewline
[460,480[ & 470 & 6 & 0.055046 & 0.073394 & 0.002752 \tabularnewline
[480,500[ & 490 & 3 & 0.027523 & 0.100917 & 0.001376 \tabularnewline
[500,520[ & 510 & 19 & 0.174312 & 0.275229 & 0.008716 \tabularnewline
[520,540[ & 530 & 15 & 0.137615 & 0.412844 & 0.006881 \tabularnewline
[540,560[ & 550 & 14 & 0.12844 & 0.541284 & 0.006422 \tabularnewline
[560,580[ & 570 & 20 & 0.183486 & 0.724771 & 0.009174 \tabularnewline
[580,600[ & 590 & 18 & 0.165138 & 0.889908 & 0.008257 \tabularnewline
[600,620[ & 610 & 6 & 0.055046 & 0.944954 & 0.002752 \tabularnewline
[620,640] & 630 & 6 & 0.055046 & 1 & 0.002752 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=118245&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][440,460[[/C][C]450[/C][C]2[/C][C]0.018349[/C][C]0.018349[/C][C]0.000917[/C][/ROW]
[ROW][C][460,480[[/C][C]470[/C][C]6[/C][C]0.055046[/C][C]0.073394[/C][C]0.002752[/C][/ROW]
[ROW][C][480,500[[/C][C]490[/C][C]3[/C][C]0.027523[/C][C]0.100917[/C][C]0.001376[/C][/ROW]
[ROW][C][500,520[[/C][C]510[/C][C]19[/C][C]0.174312[/C][C]0.275229[/C][C]0.008716[/C][/ROW]
[ROW][C][520,540[[/C][C]530[/C][C]15[/C][C]0.137615[/C][C]0.412844[/C][C]0.006881[/C][/ROW]
[ROW][C][540,560[[/C][C]550[/C][C]14[/C][C]0.12844[/C][C]0.541284[/C][C]0.006422[/C][/ROW]
[ROW][C][560,580[[/C][C]570[/C][C]20[/C][C]0.183486[/C][C]0.724771[/C][C]0.009174[/C][/ROW]
[ROW][C][580,600[[/C][C]590[/C][C]18[/C][C]0.165138[/C][C]0.889908[/C][C]0.008257[/C][/ROW]
[ROW][C][600,620[[/C][C]610[/C][C]6[/C][C]0.055046[/C][C]0.944954[/C][C]0.002752[/C][/ROW]
[ROW][C][620,640][/C][C]630[/C][C]6[/C][C]0.055046[/C][C]1[/C][C]0.002752[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=118245&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=118245&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[440,460[45020.0183490.0183490.000917
[460,480[47060.0550460.0733940.002752
[480,500[49030.0275230.1009170.001376
[500,520[510190.1743120.2752290.008716
[520,540[530150.1376150.4128440.006881
[540,560[550140.128440.5412840.006422
[560,580[570200.1834860.7247710.009174
[580,600[590180.1651380.8899080.008257
[600,620[61060.0550460.9449540.002752
[620,640]63060.05504610.002752


Figures (Output of Computation)

Input Parameters & R Code

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