Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 29 Sep 2014 15:39:41 +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/29/t14120016674ypicxg40w153t0.htm/, Retrieved Thu, 31 Oct 2024 22:48:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=236780, Retrieved Thu, 31 Oct 2024 22:48:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2014-09-29 14:39:41] [25af208440423f5cc2d7fa35cacd4ca5] [Current]
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Dataseries X:
80
100
60
60
100
100
100
90
120
100
80
160
50
120
100
80
100
80
100
80
80
60
60
50
80
20
80
60
100
90
80
90
100
80
80
140
120
100
80
80
80
100
100
60
80
140
100
100
120
90
40
90
100
100
90
120
80
100
100
90
100
100
100
90
100
50
70
80
80
90
120
100
90
80
200
120
100
80
120
90
100
120
90
100
90
90
100
100
100
80
90
60
80
120
80
100
120
140
90
50
120
60
40
120
40
100
80
80
140
100
140
120
50
100
60
100
100
80
80
20
60
160
80
160
100
100
80
60
60
90
100
90
80
100
100
100
140
160
80
90
90
80
100
100
70
100
80
100
120
80
90
140
90
100
100
100
100
90
90
140
60
100
70
90
100
100
110
120
80
100
100
120
90
120
40
40
100
80
90
100
100
60
90
100
100
110
90
120
100
80
100
100
80
120
80
120
200
80
80
110
80
100
140
100
100
60
60
80
80
100
120
80
100
100
100
80
80
100
100
120
90
80
100
100
70
70
80
100
100
120
100
80
100
80
80
80
90
70
90
80
60
100
100
80
100
60
90
100
100
60
50
100
120
90
60
90
100
50
70
120
100
100
160
100
100
60
100
80
100
100
100
80
120
80
100
120
90
100
100
100
200
80
200
100
140
80
80
80
80
80
100
100
100
80
80
80
80
100
70
100
90
90
120
120
30
80
100
120
200
90
80
40
100
100
100
100
70
100
80
100
120
70
80
100
90
90
80
80
100
80
80
80
80
100
80
40
80
100
120
100
200
120
120
200
60
100
100
90
80
90
120
100
70
90
90
120
160
100
80
40
80
40
60
80
60
80
120
50
60
50
80
60
50
100
80
100
100
100
120
80
100
60
60
90
40
60
40
80
100
80
80
150
80
80
80
160
100
100
120
100
40
80
100
50
60
100
80
90
90
80
100
100
100
60
160
80
80
60
100
60
80
100
80
120
200
80
100
80
120
120
100
100
50
100
100
100
80
80
80
60
80
100
60
100
200
120
80
80
100
50
60
80
80
140
90
60
70
120
90
50
50
80
80
60
100
60
80
80
100
70
120
80
100
100
100
80
80
100
80
90
60
60
90
80
40
100
80
80
60
50
80
20
80
60
60
100
100
100
60
100
90
100
80
70
90
100
140
100
100
100
140
120
90
120
200
60
100
100
80
100
100
100
50
60
90
100
100
100
100
60
80
80
60
140
120
80
90
260
80
100
90
80
100
100
80
100
60
80
50
60
40
100
60
120
140
100
100
100
100
100
160
160
100
100
80
100
100
90
100
120
100
100
120
100
100
120
100
100
80
90
90
80
100
90
100
90
160
100
100
100
90
80
140
80
140
100
90
100
100
100
100
100
160
100
120
100
80
100
100
120
90
90
80
60
60
100
100
80
80
60
100
60
80
90
100
60
60
70
20
60
100
70
160
100
100
80
120
80
100
100
100
90
90
100
100
120
100
100
100
100
80
80
100
100
100
100
80
120
100
90
120
80
80
120
100
100
120
80
100
100
100
100
120
70
60
90
90
100
90
90
100
60
80
90
70
140
80
80
80
100
100
120
60
100
90
100
100
80
100
100
100
90
100
100
80
90
120
60
120
100
80
100
100
140
90
80
100
80
80
70
80
90
100
40
80
100
80
80
120
100
80
60
80
100
40
80
100
90
90
100
100
60
100
80
40
100
60
100
140
100
60
100
100
120
100
40
90
80
100
80
80
100
90
70
120
80
100
80
100
80
100
80
90
50
120
50
90
100
100
100
100
120
120
40
90
90
100
80
90
80
100
80
60
100
80
100
80
120
60
160
100
80
90
90
120
80
160
80
100
80
100
80
200
200
100
100
160
120
90
120
80
100
100
120
100
100
80
70
70
110
100
90
60
160
160
50
50
70
50
100
100
70
100
90
60
100
60
60
60
100
60
50
90
80
80
100
80
50
40
60
50
60
100
80
80
60
60
120
80
100
90
90
200
60
100
60
100
90
70
200
80
200
80
80
120
100
80
90
100
200
160
100
100
100
100
120
160
100
120
80




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236780&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236780&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236780&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'Herman Ole Andreas Wold' @ wold.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[20,40[3050.0055560.0055560.000278
[40,60[50460.0511110.0566670.002556
[60,80[701060.1177780.1744440.005889
[80,100[902990.3322220.5066670.016611
[100,120[1103060.340.8466670.017
[120,140[130800.0888890.9355560.004444
[140,160[150210.0233330.9588890.001167
[160,180[170200.0222220.9811110.001111
[180,200[190000.9811110
[200,220[210160.0177780.9988890.000889
[220,240[230000.9988890
[240,260]25010.00111115.6e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[20,40[ & 30 & 5 & 0.005556 & 0.005556 & 0.000278 \tabularnewline
[40,60[ & 50 & 46 & 0.051111 & 0.056667 & 0.002556 \tabularnewline
[60,80[ & 70 & 106 & 0.117778 & 0.174444 & 0.005889 \tabularnewline
[80,100[ & 90 & 299 & 0.332222 & 0.506667 & 0.016611 \tabularnewline
[100,120[ & 110 & 306 & 0.34 & 0.846667 & 0.017 \tabularnewline
[120,140[ & 130 & 80 & 0.088889 & 0.935556 & 0.004444 \tabularnewline
[140,160[ & 150 & 21 & 0.023333 & 0.958889 & 0.001167 \tabularnewline
[160,180[ & 170 & 20 & 0.022222 & 0.981111 & 0.001111 \tabularnewline
[180,200[ & 190 & 0 & 0 & 0.981111 & 0 \tabularnewline
[200,220[ & 210 & 16 & 0.017778 & 0.998889 & 0.000889 \tabularnewline
[220,240[ & 230 & 0 & 0 & 0.998889 & 0 \tabularnewline
[240,260] & 250 & 1 & 0.001111 & 1 & 5.6e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236780&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][20,40[[/C][C]30[/C][C]5[/C][C]0.005556[/C][C]0.005556[/C][C]0.000278[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]46[/C][C]0.051111[/C][C]0.056667[/C][C]0.002556[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]106[/C][C]0.117778[/C][C]0.174444[/C][C]0.005889[/C][/ROW]
[ROW][C][80,100[[/C][C]90[/C][C]299[/C][C]0.332222[/C][C]0.506667[/C][C]0.016611[/C][/ROW]
[ROW][C][100,120[[/C][C]110[/C][C]306[/C][C]0.34[/C][C]0.846667[/C][C]0.017[/C][/ROW]
[ROW][C][120,140[[/C][C]130[/C][C]80[/C][C]0.088889[/C][C]0.935556[/C][C]0.004444[/C][/ROW]
[ROW][C][140,160[[/C][C]150[/C][C]21[/C][C]0.023333[/C][C]0.958889[/C][C]0.001167[/C][/ROW]
[ROW][C][160,180[[/C][C]170[/C][C]20[/C][C]0.022222[/C][C]0.981111[/C][C]0.001111[/C][/ROW]
[ROW][C][180,200[[/C][C]190[/C][C]0[/C][C]0[/C][C]0.981111[/C][C]0[/C][/ROW]
[ROW][C][200,220[[/C][C]210[/C][C]16[/C][C]0.017778[/C][C]0.998889[/C][C]0.000889[/C][/ROW]
[ROW][C][220,240[[/C][C]230[/C][C]0[/C][C]0[/C][C]0.998889[/C][C]0[/C][/ROW]
[ROW][C][240,260][/C][C]250[/C][C]1[/C][C]0.001111[/C][C]1[/C][C]5.6e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236780&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236780&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
[20,40[3050.0055560.0055560.000278
[40,60[50460.0511110.0566670.002556
[60,80[701060.1177780.1744440.005889
[80,100[902990.3322220.5066670.016611
[100,120[1103060.340.8466670.017
[120,140[130800.0888890.9355560.004444
[140,160[150210.0233330.9588890.001167
[160,180[170200.0222220.9811110.001111
[180,200[190000.9811110
[200,220[210160.0177780.9988890.000889
[220,240[230000.9988890
[240,260]25010.00111115.6e-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 {
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')
}