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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 27 Sep 2014 20:20:35 +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/2014/Sep/27/t1411845685d22rkey3tdxpfyh.htm/, Retrieved Fri, 10 May 2024 11:36:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=236626, Retrieved Fri, 10 May 2024 11:36:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [gemiddelde consum...] [2014-09-24 07:05:00] [486e4316d1ec63b0c6aa8f70834f8806]
- RMPD    [Histogram] [] [2014-09-27 19:20:35] [d1a83db1c928d515dd26931964d56abe] [Current]
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Dataseries X:
168.58
169.21
169.29
169.24
169.53
169.57
169.57
169.67
170.04
170.39
170.57
170.48
170.48
170.48
170.49
170.72
171.11
171.07
171.07
171.07
171.05
172.28
172.74
172.86
172.86
173.24
173.2
173.38
172.89
172.98
172.98
172.69
172.77
172.65
172.3
172.17
172.17
173.07
173.27
173.05
173.41
173.37
173.37
173.08
173.97
175.23
174.9
174.83
174.83
174.84
174.99
175.45
176.27
176.19
176.19
176.22
175.9
176.06
175.7
175.92
167.56
167.56
167.69
167.66
167.39
166.99
167.39
167.27
168.57
168.98
169.27
169.09




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' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236626&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' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236626&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' @ fisher.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[166,167[166.510.0138890.0138890.013889
[167,168[167.570.0972220.1111110.097222
[168,169[168.530.0416670.1527780.041667
[169,170[169.590.1250.2777780.125
[170,171[170.580.1111110.3888890.111111
[171,172[171.550.0694440.4583330.069444
[172,173[172.5130.1805560.6388890.180556
[173,174[173.5110.1527780.7916670.152778
[174,175[174.550.0694440.8611110.069444
[175,176[175.550.0694440.9305560.069444
[176,177]176.550.06944410.069444

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[166,167[ & 166.5 & 1 & 0.013889 & 0.013889 & 0.013889 \tabularnewline
[167,168[ & 167.5 & 7 & 0.097222 & 0.111111 & 0.097222 \tabularnewline
[168,169[ & 168.5 & 3 & 0.041667 & 0.152778 & 0.041667 \tabularnewline
[169,170[ & 169.5 & 9 & 0.125 & 0.277778 & 0.125 \tabularnewline
[170,171[ & 170.5 & 8 & 0.111111 & 0.388889 & 0.111111 \tabularnewline
[171,172[ & 171.5 & 5 & 0.069444 & 0.458333 & 0.069444 \tabularnewline
[172,173[ & 172.5 & 13 & 0.180556 & 0.638889 & 0.180556 \tabularnewline
[173,174[ & 173.5 & 11 & 0.152778 & 0.791667 & 0.152778 \tabularnewline
[174,175[ & 174.5 & 5 & 0.069444 & 0.861111 & 0.069444 \tabularnewline
[175,176[ & 175.5 & 5 & 0.069444 & 0.930556 & 0.069444 \tabularnewline
[176,177] & 176.5 & 5 & 0.069444 & 1 & 0.069444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236626&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][166,167[[/C][C]166.5[/C][C]1[/C][C]0.013889[/C][C]0.013889[/C][C]0.013889[/C][/ROW]
[ROW][C][167,168[[/C][C]167.5[/C][C]7[/C][C]0.097222[/C][C]0.111111[/C][C]0.097222[/C][/ROW]
[ROW][C][168,169[[/C][C]168.5[/C][C]3[/C][C]0.041667[/C][C]0.152778[/C][C]0.041667[/C][/ROW]
[ROW][C][169,170[[/C][C]169.5[/C][C]9[/C][C]0.125[/C][C]0.277778[/C][C]0.125[/C][/ROW]
[ROW][C][170,171[[/C][C]170.5[/C][C]8[/C][C]0.111111[/C][C]0.388889[/C][C]0.111111[/C][/ROW]
[ROW][C][171,172[[/C][C]171.5[/C][C]5[/C][C]0.069444[/C][C]0.458333[/C][C]0.069444[/C][/ROW]
[ROW][C][172,173[[/C][C]172.5[/C][C]13[/C][C]0.180556[/C][C]0.638889[/C][C]0.180556[/C][/ROW]
[ROW][C][173,174[[/C][C]173.5[/C][C]11[/C][C]0.152778[/C][C]0.791667[/C][C]0.152778[/C][/ROW]
[ROW][C][174,175[[/C][C]174.5[/C][C]5[/C][C]0.069444[/C][C]0.861111[/C][C]0.069444[/C][/ROW]
[ROW][C][175,176[[/C][C]175.5[/C][C]5[/C][C]0.069444[/C][C]0.930556[/C][C]0.069444[/C][/ROW]
[ROW][C][176,177][/C][C]176.5[/C][C]5[/C][C]0.069444[/C][C]1[/C][C]0.069444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236626&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
[166,167[166.510.0138890.0138890.013889
[167,168[167.570.0972220.1111110.097222
[168,169[168.530.0416670.1527780.041667
[169,170[169.590.1250.2777780.125
[170,171[170.580.1111110.3888890.111111
[171,172[171.550.0694440.4583330.069444
[172,173[172.5130.1805560.6388890.180556
[173,174[173.5110.1527780.7916670.152778
[174,175[174.550.0694440.8611110.069444
[175,176[175.550.0694440.9305560.069444
[176,177]176.550.06944410.069444



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')
}