Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 22 Sep 2014 12:01:31 +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/22/t141138379457dppb3c2l2zbom.htm/, Retrieved Fri, 10 May 2024 14:59:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=236047, Retrieved Fri, 10 May 2024 14:59:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsGemiddelde consumptieprijzen per product: aankoop van voertuigen - fietsen
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Gemiddelde consum...] [2014-09-22 11:01:31] [6e93958bb59fd6ca90246553243cf8d9] [Current]
Feedback Forum

Post a new message
Dataseries X:
389,09
391,76
390,96
391,76
392,8
393,06
393,06
393,26
393,87
394,47
394,57
394,57
394,57
399,57
406,13
407,03
409,46
409,9
409,9
410,14
410,54
410,69
410,79
410,97
410,97
413,8
423,31
423,85
426,6
426,26
426,26
426,32
427,14
427,55
428,29
428,8
428,8
434,87
435,66
440,75
440,99
441,04
441,04
441,88
441,92
442,48
442,81
442,81
442,81
447,19
446,52
448,57
448,71
448,73
449,07
449,03
448,68
450,08
449,96
449,96
449,96
452,56
455,31
456,2
456,75
457,63
457,63
457,65
458,32
459,64
460,16
459,89





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 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=236047&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]'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=236047&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236047&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'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
[380,390[38510.0138890.0138890.001389
[390,400[395130.1805560.1944440.018056
[400,410[40550.0694440.2638890.006944
[410,420[41570.0972220.3611110.009722
[420,430[425110.1527780.5138890.015278
[430,440[43520.0277780.5416670.002778
[440,450[445210.2916670.8333330.029167
[450,460[455110.1527780.9861110.015278
[460,470]46510.01388910.001389

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[380,390[ & 385 & 1 & 0.013889 & 0.013889 & 0.001389 \tabularnewline
[390,400[ & 395 & 13 & 0.180556 & 0.194444 & 0.018056 \tabularnewline
[400,410[ & 405 & 5 & 0.069444 & 0.263889 & 0.006944 \tabularnewline
[410,420[ & 415 & 7 & 0.097222 & 0.361111 & 0.009722 \tabularnewline
[420,430[ & 425 & 11 & 0.152778 & 0.513889 & 0.015278 \tabularnewline
[430,440[ & 435 & 2 & 0.027778 & 0.541667 & 0.002778 \tabularnewline
[440,450[ & 445 & 21 & 0.291667 & 0.833333 & 0.029167 \tabularnewline
[450,460[ & 455 & 11 & 0.152778 & 0.986111 & 0.015278 \tabularnewline
[460,470] & 465 & 1 & 0.013889 & 1 & 0.001389 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236047&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][380,390[[/C][C]385[/C][C]1[/C][C]0.013889[/C][C]0.013889[/C][C]0.001389[/C][/ROW]
[ROW][C][390,400[[/C][C]395[/C][C]13[/C][C]0.180556[/C][C]0.194444[/C][C]0.018056[/C][/ROW]
[ROW][C][400,410[[/C][C]405[/C][C]5[/C][C]0.069444[/C][C]0.263889[/C][C]0.006944[/C][/ROW]
[ROW][C][410,420[[/C][C]415[/C][C]7[/C][C]0.097222[/C][C]0.361111[/C][C]0.009722[/C][/ROW]
[ROW][C][420,430[[/C][C]425[/C][C]11[/C][C]0.152778[/C][C]0.513889[/C][C]0.015278[/C][/ROW]
[ROW][C][430,440[[/C][C]435[/C][C]2[/C][C]0.027778[/C][C]0.541667[/C][C]0.002778[/C][/ROW]
[ROW][C][440,450[[/C][C]445[/C][C]21[/C][C]0.291667[/C][C]0.833333[/C][C]0.029167[/C][/ROW]
[ROW][C][450,460[[/C][C]455[/C][C]11[/C][C]0.152778[/C][C]0.986111[/C][C]0.015278[/C][/ROW]
[ROW][C][460,470][/C][C]465[/C][C]1[/C][C]0.013889[/C][C]1[/C][C]0.001389[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236047&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236047&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
[380,390[38510.0138890.0138890.001389
[390,400[395130.1805560.1944440.018056
[400,410[40550.0694440.2638890.006944
[410,420[41570.0972220.3611110.009722
[420,430[425110.1527780.5138890.015278
[430,440[43520.0277780.5416670.002778
[440,450[445210.2916670.8333330.029167
[450,460[455110.1527780.9861110.015278
[460,470]46510.01388910.001389



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')
}