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Author's title

bezettingsgraad bedden toeristische sector belgië frequentietabel opgave 1...

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 05 Oct 2010 11:03:16 +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/2010/Oct/05/t12862768082opz8vt5coivlpb.htm/, Retrieved Sat, 27 Apr 2024 15:18:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=81392, Retrieved Sat, 27 Apr 2024 15:18:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W1
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Bezettingsgraad b...] [2010-10-04 15:17:36] [a8df0d1af66a7f69bd895162e6e9e24a]
- RMPD    [Histogram] [bezettingsgraad b...] [2010-10-05 11:03:16] [d5f8481d835a4a90565680e4111cba41] [Current]
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Dataseries X:
24.3
29.4
31.8
36.7
37.1
37.7
39.4
43.3
39.6
34.3
32
29.6
22.3
28.9
31.7
34.2
38.6
37.2
38.8
43.4
38.8
36.3
33
29.2
22.64
28.44
30.14
34.39
36.82
36.74
38.9
42.8
39.09
37.49
33.17
30.98
21.2
27.8
29
35.4
37.5
34.7
38.4
39.9
35.9
34.7
30.4
29
21.5
28
29.3
34.3
36.6
36.2
37.5
41.6
39.4
37.3
32.7
30.7
22.9
29.1
29.5
37.1
37.7
38.4
39.4
40.6
39.7
36.6
32.8
31.6
24.1
30.3
31.8
38.7
37.8
38.4
40.7
43.8
41.5
39.3
35.9
33.4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=81392&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=81392&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=81392&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[20,25[22.570.0833330.0833330.016667
[25,30[27.5120.1428570.226190.028571
[30,35[32.5210.250.476190.05
[35,40[37.5360.4285710.9047620.085714
[40,45]42.580.09523810.019048

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[20,25[ & 22.5 & 7 & 0.083333 & 0.083333 & 0.016667 \tabularnewline
[25,30[ & 27.5 & 12 & 0.142857 & 0.22619 & 0.028571 \tabularnewline
[30,35[ & 32.5 & 21 & 0.25 & 0.47619 & 0.05 \tabularnewline
[35,40[ & 37.5 & 36 & 0.428571 & 0.904762 & 0.085714 \tabularnewline
[40,45] & 42.5 & 8 & 0.095238 & 1 & 0.019048 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=81392&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][20,25[[/C][C]22.5[/C][C]7[/C][C]0.083333[/C][C]0.083333[/C][C]0.016667[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]12[/C][C]0.142857[/C][C]0.22619[/C][C]0.028571[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]21[/C][C]0.25[/C][C]0.47619[/C][C]0.05[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]36[/C][C]0.428571[/C][C]0.904762[/C][C]0.085714[/C][/ROW]
[ROW][C][40,45][/C][C]42.5[/C][C]8[/C][C]0.095238[/C][C]1[/C][C]0.019048[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=81392&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=81392&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
[20,25[22.570.0833330.0833330.016667
[25,30[27.5120.1428570.226190.028571
[30,35[32.5210.250.476190.05
[35,40[37.5360.4285710.9047620.085714
[40,45]42.580.09523810.019048



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 {
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')
}