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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 13 Feb 2012 07:24:33 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Feb/13/t1329136161vg5mn0e3s6zdj1j.htm/, Retrieved Thu, 31 Oct 2024 23:45:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=162197, Retrieved Thu, 31 Oct 2024 23:45:17 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDG2011W2MO
Estimated Impact169
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Frequentietabel m...] [2012-02-13 12:24:33] [aa59cfa385e119596867d158cdccc7ef] [Current]
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Dataseries X:
25
25
25
25
29
30
30
29
35
30
30
30
29
30
30
26
30
30
30
35
30
30
30
50
25
29
30
25
30
30
25
42
29
15
29
30
25
20
10
30
29
30
50
25
30
30
25
50
29
30
30
30
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35
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29
26
23
25
30
30
30
30
20
29
25
25
28
30
30
25
30
31
30
29
45
30
30
35
30
30
25
50
40
20
35
22
30
25
30
30
29
50
45
30
26
30
29
35
20
29
25
30
45
35
30
30
40
20
26
29
20
25
30
30
25
30
23
25
30
30
40
30
40
35
40
30
25
33
30
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30
35
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25
27
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30
35
20
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23
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25
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40
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35
20
29
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35
15
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29
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20
35
50
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18
15
30
23
29
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35
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23
30
25
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40
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40
37
20
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32
35
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45
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29
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35
25
21
30
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30
15
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30
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25
30
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25
25
40
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33
40
26
30
37
25
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29
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30
22
25
30
40
30
29
25
30
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29
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30
35
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35
30
12
15
25
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20
30
35
35
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20
29
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30
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35
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35
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35
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32
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25
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30
30
60
20
30
35
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40
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26
18
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35
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35
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20
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25
47
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20
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25
40
29
40
29
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30
35
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20
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24
30
40
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15
35
18
30
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34
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23
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1
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50
20
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30
29
35
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20
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21
29
35
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30
35
26
30
25
25
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25
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29
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26
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50
25
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40
30
32
25
35
30
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20
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26
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30
30
26
35
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26
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15
40
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25
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25
25
30
20
18
25
30
29
13
27
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25
30
35
29
30
29
30
30
25
45
29
30
30
25
25
29
30
30
30
29
30
23
35
35
10
32
29
45
30
29
30
15
50
35
25
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30
40
29
25
30
25
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35
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15
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35
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30
30

30
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25
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35
25
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25
50
20
45
25
35
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40
35
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30
30
23
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25
30
15




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=162197&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=162197&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=162197&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'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,5[2.510.0009820.0009820.000196
[5,10[7.5000.0009820
[10,15[12.540.0039290.0049120.000786
[15,20[17.5200.0196460.0245580.003929
[20,25[22.5710.0697450.0943030.013949
[25,30[27.52490.2445970.33890.048919
[30,35[32.54870.4783890.8172890.095678
[35,40[37.5880.0864440.9037330.017289
[40,45[42.5550.0540280.957760.010806
[45,50[47.590.0088410.9666010.001768
[50,55[52.5330.0324170.9990180.006483
[55,60]57.510.00098210.000196

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,5[ & 2.5 & 1 & 0.000982 & 0.000982 & 0.000196 \tabularnewline
[5,10[ & 7.5 & 0 & 0 & 0.000982 & 0 \tabularnewline
[10,15[ & 12.5 & 4 & 0.003929 & 0.004912 & 0.000786 \tabularnewline
[15,20[ & 17.5 & 20 & 0.019646 & 0.024558 & 0.003929 \tabularnewline
[20,25[ & 22.5 & 71 & 0.069745 & 0.094303 & 0.013949 \tabularnewline
[25,30[ & 27.5 & 249 & 0.244597 & 0.3389 & 0.048919 \tabularnewline
[30,35[ & 32.5 & 487 & 0.478389 & 0.817289 & 0.095678 \tabularnewline
[35,40[ & 37.5 & 88 & 0.086444 & 0.903733 & 0.017289 \tabularnewline
[40,45[ & 42.5 & 55 & 0.054028 & 0.95776 & 0.010806 \tabularnewline
[45,50[ & 47.5 & 9 & 0.008841 & 0.966601 & 0.001768 \tabularnewline
[50,55[ & 52.5 & 33 & 0.032417 & 0.999018 & 0.006483 \tabularnewline
[55,60] & 57.5 & 1 & 0.000982 & 1 & 0.000196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=162197&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][0,5[[/C][C]2.5[/C][C]1[/C][C]0.000982[/C][C]0.000982[/C][C]0.000196[/C][/ROW]
[ROW][C][5,10[[/C][C]7.5[/C][C]0[/C][C]0[/C][C]0.000982[/C][C]0[/C][/ROW]
[ROW][C][10,15[[/C][C]12.5[/C][C]4[/C][C]0.003929[/C][C]0.004912[/C][C]0.000786[/C][/ROW]
[ROW][C][15,20[[/C][C]17.5[/C][C]20[/C][C]0.019646[/C][C]0.024558[/C][C]0.003929[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]71[/C][C]0.069745[/C][C]0.094303[/C][C]0.013949[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]249[/C][C]0.244597[/C][C]0.3389[/C][C]0.048919[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]487[/C][C]0.478389[/C][C]0.817289[/C][C]0.095678[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]88[/C][C]0.086444[/C][C]0.903733[/C][C]0.017289[/C][/ROW]
[ROW][C][40,45[[/C][C]42.5[/C][C]55[/C][C]0.054028[/C][C]0.95776[/C][C]0.010806[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]9[/C][C]0.008841[/C][C]0.966601[/C][C]0.001768[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]33[/C][C]0.032417[/C][C]0.999018[/C][C]0.006483[/C][/ROW]
[ROW][C][55,60][/C][C]57.5[/C][C]1[/C][C]0.000982[/C][C]1[/C][C]0.000196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=162197&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=162197&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
[0,5[2.510.0009820.0009820.000196
[5,10[7.5000.0009820
[10,15[12.540.0039290.0049120.000786
[15,20[17.5200.0196460.0245580.003929
[20,25[22.5710.0697450.0943030.013949
[25,30[27.52490.2445970.33890.048919
[30,35[32.54870.4783890.8172890.095678
[35,40[37.5880.0864440.9037330.017289
[40,45[42.5550.0540280.957760.010806
[45,50[47.590.0088410.9666010.001768
[50,55[52.5330.0324170.9990180.006483
[55,60]57.510.00098210.000196



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')
}