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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, 22 Feb 2016 17:21:49 +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/2016/Feb/22/t1456161935tqhx07nuwvjhy4y.htm/, Retrieved Fri, 03 May 2024 12:41:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=292409, Retrieved Fri, 03 May 2024 12:41:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Uitvoer België] [2016-02-08 16:31:30] [26095a9ae1e69517a2e1971137f70057]
- RMPD    [Histogram] [Maximumprijs bios...] [2016-02-22 17:21:49] [30ac29e28bcab64021946a7872e1db5d] [Current]
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Dataseries X:
13566.7
13941.5
14964.1
14086
13505.1
15300.4
14725.2
12484.9
16082.6
15915.8
15916.1
15713
14746
15253.2
18384.3
16848.5
16485.5
19257.1
17093.4
15700.1
19124.3
18640.8
18439.2
17106.3
18347.7
19372.7
22263.8
19422.9
21268.6
20310
19256
17535.9
19857.4
19628.4
19727.5
18112.2
18889.3
20516.1
22317
19768.8
20015.8
20260.5
19434.3
17910
19134.4
20880.1
19680
17493.4
19087.8
19064.6
21191
20503.9
20364.1
19860.4
20924.1
17018.8
20607.4
21500.2
19868.3
18801.9
19787.5
19936.2
21047.6
21034.4
20132.8
20725.3
20827.8
16992.3
21818.2
21841.4
19252.2
17933.7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292409&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292409&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292409&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 time0 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[12000,13000[1250010.0138890.0138891.4e-05
[13000,14000[1350030.0416670.0555564.2e-05
[14000,15000[1450040.0555560.1111115.6e-05
[15000,16000[1550060.0833330.1944448.3e-05
[16000,17000[1650040.0555560.255.6e-05
[17000,18000[1750070.0972220.3472229.7e-05
[18000,19000[1850070.0972220.4444449.7e-05
[19000,20000[19500190.2638890.7083330.000264
[20000,21000[20500120.1666670.8750.000167
[21000,22000[2150070.0972220.9722229.7e-05
[22000,23000]2250020.02777812.8e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[12000,13000[ & 12500 & 1 & 0.013889 & 0.013889 & 1.4e-05 \tabularnewline
[13000,14000[ & 13500 & 3 & 0.041667 & 0.055556 & 4.2e-05 \tabularnewline
[14000,15000[ & 14500 & 4 & 0.055556 & 0.111111 & 5.6e-05 \tabularnewline
[15000,16000[ & 15500 & 6 & 0.083333 & 0.194444 & 8.3e-05 \tabularnewline
[16000,17000[ & 16500 & 4 & 0.055556 & 0.25 & 5.6e-05 \tabularnewline
[17000,18000[ & 17500 & 7 & 0.097222 & 0.347222 & 9.7e-05 \tabularnewline
[18000,19000[ & 18500 & 7 & 0.097222 & 0.444444 & 9.7e-05 \tabularnewline
[19000,20000[ & 19500 & 19 & 0.263889 & 0.708333 & 0.000264 \tabularnewline
[20000,21000[ & 20500 & 12 & 0.166667 & 0.875 & 0.000167 \tabularnewline
[21000,22000[ & 21500 & 7 & 0.097222 & 0.972222 & 9.7e-05 \tabularnewline
[22000,23000] & 22500 & 2 & 0.027778 & 1 & 2.8e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292409&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][12000,13000[[/C][C]12500[/C][C]1[/C][C]0.013889[/C][C]0.013889[/C][C]1.4e-05[/C][/ROW]
[ROW][C][13000,14000[[/C][C]13500[/C][C]3[/C][C]0.041667[/C][C]0.055556[/C][C]4.2e-05[/C][/ROW]
[ROW][C][14000,15000[[/C][C]14500[/C][C]4[/C][C]0.055556[/C][C]0.111111[/C][C]5.6e-05[/C][/ROW]
[ROW][C][15000,16000[[/C][C]15500[/C][C]6[/C][C]0.083333[/C][C]0.194444[/C][C]8.3e-05[/C][/ROW]
[ROW][C][16000,17000[[/C][C]16500[/C][C]4[/C][C]0.055556[/C][C]0.25[/C][C]5.6e-05[/C][/ROW]
[ROW][C][17000,18000[[/C][C]17500[/C][C]7[/C][C]0.097222[/C][C]0.347222[/C][C]9.7e-05[/C][/ROW]
[ROW][C][18000,19000[[/C][C]18500[/C][C]7[/C][C]0.097222[/C][C]0.444444[/C][C]9.7e-05[/C][/ROW]
[ROW][C][19000,20000[[/C][C]19500[/C][C]19[/C][C]0.263889[/C][C]0.708333[/C][C]0.000264[/C][/ROW]
[ROW][C][20000,21000[[/C][C]20500[/C][C]12[/C][C]0.166667[/C][C]0.875[/C][C]0.000167[/C][/ROW]
[ROW][C][21000,22000[[/C][C]21500[/C][C]7[/C][C]0.097222[/C][C]0.972222[/C][C]9.7e-05[/C][/ROW]
[ROW][C][22000,23000][/C][C]22500[/C][C]2[/C][C]0.027778[/C][C]1[/C][C]2.8e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292409&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292409&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
[12000,13000[1250010.0138890.0138891.4e-05
[13000,14000[1350030.0416670.0555564.2e-05
[14000,15000[1450040.0555560.1111115.6e-05
[15000,16000[1550060.0833330.1944448.3e-05
[16000,17000[1650040.0555560.255.6e-05
[17000,18000[1750070.0972220.3472229.7e-05
[18000,19000[1850070.0972220.4444449.7e-05
[19000,20000[19500190.2638890.7083330.000264
[20000,21000[20500120.1666670.8750.000167
[21000,22000[2150070.0972220.9722229.7e-05
[22000,23000]2250020.02777812.8e-05



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 {
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,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')
}