Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 16 Dec 2014 15:16:38 +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/2014/Dec/16/t1418743020wd7e4rpipfa06p9.htm/, Retrieved Thu, 16 May 2024 17:00:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269703, Retrieved Thu, 16 May 2024 17:00:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [] [2014-12-09 12:44:29] [7b949ef3605c038fc6e10efeab34f433]
- R     [Histogram] [] [2014-12-09 12:51:41] [7b949ef3605c038fc6e10efeab34f433]
-    D    [Histogram] [] [2014-12-16 15:14:55] [7b949ef3605c038fc6e10efeab34f433]
-    D        [Histogram] [] [2014-12-16 15:16:38] [aa823bdb4d51626f3fbc68989a46faf3] [Current]
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Dataseries X:
0,42
0,58
0,89
0,55
0,36
0,58
0,59
0,8
0,74
0,43
0,5
0,67
0,2
0,84
0,65
0,53
0,61
0,73
0,68
0,26
0,72
0,24
0,71
0,59
0,27
0,57
0,51
0,69
0,69
0,5
0,63
0,65
0,54
0,69
0,52
0,53
0,74
0,73
0,75
0,7
0,69
0,57
0,14
0,42
0,48
0,27
0,21
0,41
0,56
0,44
0,52
0,59
0,96
0,43
0,66
0,68
0,78
0,6
0,81
0,51
0,86
0,67
0,85
0,75
0,83
0,82
0,58
0,72
0,89
0,51
0,75
0,59
0,57
0,72
0,38
0,45
0,55
0,73
0,73
0,73
0,71
0,38
0,79
0,32
0,62
0,42
0,45
0,97
0,08
0,49
0,66
0,55
0,49
0,69
0,68
0
0,48
0,77
0,5
0,47
0,74
0,82
0,46
0,58
0,77
0,76
0,61
0,37
0,47
0,55
0,85
0,79
0,7
0,7
0,46
0,76
0,74
0,47
0,44
0,75
0,78
0,26
0,55
0,49
0,81
0,45
0,39
0,89
0,66
0,34
0,84
0,05
0,79
0,6
0,58
0,66
0,47
0,56
0,62
0,5
0,85
0,65
0,55
0,66
0,57
0,63
0,61
0,5
0,84
0,33
0,5
0,44
0,72
0,64
0,44
0,52
0,63
0,53
0,65
0,84
0,78
0,59
0,78
0,56
0,74
0,71
0,69
0,88
0,43
0,56
0,51
0,78
0,59
0,87
0,6
0,57
0,86
0,53
0,39
0,51
0,64
0,56
0,64
0,59
0,7
0,71
0,19
0,54
0,87
0,65
0,48
0,67
0,5
0,36
0,83
0,46
0,42
0,67
0,63
0,61
0,51
0,86
0,86
0,56
0,64
0,65
0,4
0,83
0,71
0,72
0,56
0,5
0,59
0,8
0,76
0,54
0,63
0,72
0,45
0,61
0,49
0,7
0,78
0,75
0,42
0,8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269703&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269703&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269703&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 Maurice George Kendall' @ kendall.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,0.1[0.0530.0132740.0132740.132743
[0.1,0.2[0.1520.008850.0221240.088496
[0.2,0.3[0.2570.0309730.0530970.309735
[0.3,0.4[0.35100.0442480.0973450.442478
[0.4,0.5[0.45320.1415930.2389381.415929
[0.5,0.6[0.55550.2433630.4823012.433628
[0.6,0.7[0.65430.1902650.6725661.902655
[0.7,0.8[0.75450.1991150.8716811.99115
[0.8,0.9[0.85270.1194690.991151.19469
[0.9,1]0.9520.0088510.088496

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,0.1[ & 0.05 & 3 & 0.013274 & 0.013274 & 0.132743 \tabularnewline
[0.1,0.2[ & 0.15 & 2 & 0.00885 & 0.022124 & 0.088496 \tabularnewline
[0.2,0.3[ & 0.25 & 7 & 0.030973 & 0.053097 & 0.309735 \tabularnewline
[0.3,0.4[ & 0.35 & 10 & 0.044248 & 0.097345 & 0.442478 \tabularnewline
[0.4,0.5[ & 0.45 & 32 & 0.141593 & 0.238938 & 1.415929 \tabularnewline
[0.5,0.6[ & 0.55 & 55 & 0.243363 & 0.482301 & 2.433628 \tabularnewline
[0.6,0.7[ & 0.65 & 43 & 0.190265 & 0.672566 & 1.902655 \tabularnewline
[0.7,0.8[ & 0.75 & 45 & 0.199115 & 0.871681 & 1.99115 \tabularnewline
[0.8,0.9[ & 0.85 & 27 & 0.119469 & 0.99115 & 1.19469 \tabularnewline
[0.9,1] & 0.95 & 2 & 0.00885 & 1 & 0.088496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269703&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][0,0.1[[/C][C]0.05[/C][C]3[/C][C]0.013274[/C][C]0.013274[/C][C]0.132743[/C][/ROW]
[ROW][C][0.1,0.2[[/C][C]0.15[/C][C]2[/C][C]0.00885[/C][C]0.022124[/C][C]0.088496[/C][/ROW]
[ROW][C][0.2,0.3[[/C][C]0.25[/C][C]7[/C][C]0.030973[/C][C]0.053097[/C][C]0.309735[/C][/ROW]
[ROW][C][0.3,0.4[[/C][C]0.35[/C][C]10[/C][C]0.044248[/C][C]0.097345[/C][C]0.442478[/C][/ROW]
[ROW][C][0.4,0.5[[/C][C]0.45[/C][C]32[/C][C]0.141593[/C][C]0.238938[/C][C]1.415929[/C][/ROW]
[ROW][C][0.5,0.6[[/C][C]0.55[/C][C]55[/C][C]0.243363[/C][C]0.482301[/C][C]2.433628[/C][/ROW]
[ROW][C][0.6,0.7[[/C][C]0.65[/C][C]43[/C][C]0.190265[/C][C]0.672566[/C][C]1.902655[/C][/ROW]
[ROW][C][0.7,0.8[[/C][C]0.75[/C][C]45[/C][C]0.199115[/C][C]0.871681[/C][C]1.99115[/C][/ROW]
[ROW][C][0.8,0.9[[/C][C]0.85[/C][C]27[/C][C]0.119469[/C][C]0.99115[/C][C]1.19469[/C][/ROW]
[ROW][C][0.9,1][/C][C]0.95[/C][C]2[/C][C]0.00885[/C][C]1[/C][C]0.088496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269703&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269703&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
[0,0.1[0.0530.0132740.0132740.132743
[0.1,0.2[0.1520.008850.0221240.088496
[0.2,0.3[0.2570.0309730.0530970.309735
[0.3,0.4[0.35100.0442480.0973450.442478
[0.4,0.5[0.45320.1415930.2389381.415929
[0.5,0.6[0.55550.2433630.4823012.433628
[0.6,0.7[0.65430.1902650.6725661.902655
[0.7,0.8[0.75450.1991150.8716811.99115
[0.8,0.9[0.85270.1194690.991151.19469
[0.9,1]0.9520.0088510.088496



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')
}