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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 16 Aug 2017 17:39:28 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/16/t15028980234l5o9phgylwsjnc.htm/, Retrieved Sun, 12 May 2024 05:54:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307428, Retrieved Sun, 12 May 2024 05:54:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Frequentietabel: ...] [2017-08-16 15:39:28] [de0d54ff4aa383cef5d270d23e3500df] [Current]
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Dataseries X:
336960.00
324480.00
343200.00
274560.00
355680.00
349440.00
374400.00
386880.00
430560.00
374400.00
355680.00
443040.00
374400.00
280800.00
330720.00
249600.00
349440.00
287040.00
380640.00
343200.00
361920.00
405600.00
399360.00
474240.00
343200.00
287040.00
318240.00
230880.00
330720.00
255840.00
361920.00
343200.00
305760.00
436800.00
393120.00
449280.00
336960.00
312000.00
280800.00
230880.00
305760.00
274560.00
374400.00
361920.00
312000.00
418080.00
386880.00
499200.00
399360.00
243360.00
243360.00
243360.00
287040.00
287040.00
386880.00
355680.00
318240.00
399360.00
368160.00
530400.00
418080.00
243360.00
255840.00
212160.00
293280.00
336960.00
424320.00
418080.00
336960.00
393120.00
349440.00
499200.00
380640.00
305760.00
274560.00
205920.00
305760.00
368160.00
430560.00
405600.00
299520.00
430560.00
336960.00
517920.00
430560.00
312000.00
287040.00
193440.00
305760.00
293280.00
443040.00
443040.00
336960.00
436800.00
324480.00
505440.00
430560.00
318240.00
243360.00
168480.00
330720.00
318240.00
418080.00
480480.00
355680.00
399360.00
299520.00
517920.00




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307428&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307428&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307428&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[150000,200000[17500020.0185190.0185190
[200000,250000[225000100.0925930.1111112e-06
[250000,300000[275000160.1481480.2592593e-06
[300000,350000[325000300.2777780.5370376e-06
[350000,400000[375000240.2222220.7592594e-06
[400000,450000[425000180.1666670.9259263e-06
[450000,500000[47500040.0370370.9629631e-06
[500000,550000]52500040.03703711e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[150000,200000[ & 175000 & 2 & 0.018519 & 0.018519 & 0 \tabularnewline
[200000,250000[ & 225000 & 10 & 0.092593 & 0.111111 & 2e-06 \tabularnewline
[250000,300000[ & 275000 & 16 & 0.148148 & 0.259259 & 3e-06 \tabularnewline
[300000,350000[ & 325000 & 30 & 0.277778 & 0.537037 & 6e-06 \tabularnewline
[350000,400000[ & 375000 & 24 & 0.222222 & 0.759259 & 4e-06 \tabularnewline
[400000,450000[ & 425000 & 18 & 0.166667 & 0.925926 & 3e-06 \tabularnewline
[450000,500000[ & 475000 & 4 & 0.037037 & 0.962963 & 1e-06 \tabularnewline
[500000,550000] & 525000 & 4 & 0.037037 & 1 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307428&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][150000,200000[[/C][C]175000[/C][C]2[/C][C]0.018519[/C][C]0.018519[/C][C]0[/C][/ROW]
[ROW][C][200000,250000[[/C][C]225000[/C][C]10[/C][C]0.092593[/C][C]0.111111[/C][C]2e-06[/C][/ROW]
[ROW][C][250000,300000[[/C][C]275000[/C][C]16[/C][C]0.148148[/C][C]0.259259[/C][C]3e-06[/C][/ROW]
[ROW][C][300000,350000[[/C][C]325000[/C][C]30[/C][C]0.277778[/C][C]0.537037[/C][C]6e-06[/C][/ROW]
[ROW][C][350000,400000[[/C][C]375000[/C][C]24[/C][C]0.222222[/C][C]0.759259[/C][C]4e-06[/C][/ROW]
[ROW][C][400000,450000[[/C][C]425000[/C][C]18[/C][C]0.166667[/C][C]0.925926[/C][C]3e-06[/C][/ROW]
[ROW][C][450000,500000[[/C][C]475000[/C][C]4[/C][C]0.037037[/C][C]0.962963[/C][C]1e-06[/C][/ROW]
[ROW][C][500000,550000][/C][C]525000[/C][C]4[/C][C]0.037037[/C][C]1[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307428&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307428&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
[150000,200000[17500020.0185190.0185190
[200000,250000[225000100.0925930.1111112e-06
[250000,300000[275000160.1481480.2592593e-06
[300000,350000[325000300.2777780.5370376e-06
[350000,400000[375000240.2222220.7592594e-06
[400000,450000[425000180.1666670.9259263e-06
[450000,500000[47500040.0370370.9629631e-06
[500000,550000]52500040.03703711e-06



Parameters (Session):
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,'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')
}