Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationThu, 02 Dec 2010 17:39:38 +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/2010/Dec/02/t1291311505iy0z6gcmaraujix.htm/, Retrieved Sun, 05 May 2024 12:27:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104381, Retrieved Sun, 05 May 2024 12:27:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Bad example of Hi...] [2010-09-25 09:28:23] [b98453cac15ba1066b407e146608df68]
-    D  [Histogram] [Paper - histogram...] [2010-11-12 20:48:53] [6ff9fb24bdca608d2f4f1f9db3f6445e]
-   P     [Histogram] [Paper - histogram...] [2010-11-12 21:15:41] [6ff9fb24bdca608d2f4f1f9db3f6445e]
- R PD      [Histogram] [PAPER BAEYENS (Hi...] [2010-12-02 16:48:48] [e4076051fbfb461c886b1e223cd7862f]
-   PD          [Histogram] [PAPER BAEYENS (Hi...] [2010-12-02 17:39:38] [2953e4eb3235e2fd3d6373a16d27c72f] [Current]
- RMPD            [Variability] [PAPER BAEYENS (Va...] [2010-12-04 13:37:40] [e4076051fbfb461c886b1e223cd7862f]
- RMP             [Variability] [PAPER BAEYENS (Va...] [2010-12-04 13:44:36] [e4076051fbfb461c886b1e223cd7862f]
- RMPD            [Notched Boxplots] [PAPER BAEYENS (No...] [2010-12-04 14:05:13] [e4076051fbfb461c886b1e223cd7862f]
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Dataseries X:
5
3
0
7
4
1
6
3
12
0
5
6
6
6
2
1
5
7
3
3
3
7
8
6
3
5
5
10
2
6
4
6
8
4
5
10
6
7
4
10
4
3
3
3
3
7
15
0
0
4
5
5
2
3
0
9
2
7
7
0
0
10
2
1
8
6
11
3
8
6
9
9
8
8
7
6
5
4
6
3
2
12
8
5
9
6
5
2
4
7
5
6
7
8
6
0
1
5
5
5
7
7
1
3
4
8
6
6
2
2
3
3
0
2
8
8
0
5
9
6
6
3
9
7
8
0
7
0
5
0
14
5
2
8
4
2
6
3
5
9
3
3
0
10
4
2
3
10
7
0
6
8
0
4
10
5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104381&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104381&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104381&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'Gwilym Jenkins' @ 72.249.127.135







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,1[0.5160.1025640.1025640.102564
[1,2[1.550.0320510.1346150.032051
[2,3[2.5130.0833330.2179490.083333
[3,4[3.5210.1346150.3525640.134615
[4,5[4.5120.0769230.4294870.076923
[5,6[5.5200.1282050.5576920.128205
[6,7[6.5210.1346150.6923080.134615
[7,8[7.5150.0961540.7884620.096154
[8,9[8.5140.0897440.8782050.089744
[9,10[9.570.0448720.9230770.044872
[10,11[10.570.0448720.9679490.044872
[11,12[11.510.006410.9743590.00641
[12,13[12.520.0128210.9871790.012821
[13,14[13.5000.9871790
[14,15]14.520.01282110.012821

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,1[ & 0.5 & 16 & 0.102564 & 0.102564 & 0.102564 \tabularnewline
[1,2[ & 1.5 & 5 & 0.032051 & 0.134615 & 0.032051 \tabularnewline
[2,3[ & 2.5 & 13 & 0.083333 & 0.217949 & 0.083333 \tabularnewline
[3,4[ & 3.5 & 21 & 0.134615 & 0.352564 & 0.134615 \tabularnewline
[4,5[ & 4.5 & 12 & 0.076923 & 0.429487 & 0.076923 \tabularnewline
[5,6[ & 5.5 & 20 & 0.128205 & 0.557692 & 0.128205 \tabularnewline
[6,7[ & 6.5 & 21 & 0.134615 & 0.692308 & 0.134615 \tabularnewline
[7,8[ & 7.5 & 15 & 0.096154 & 0.788462 & 0.096154 \tabularnewline
[8,9[ & 8.5 & 14 & 0.089744 & 0.878205 & 0.089744 \tabularnewline
[9,10[ & 9.5 & 7 & 0.044872 & 0.923077 & 0.044872 \tabularnewline
[10,11[ & 10.5 & 7 & 0.044872 & 0.967949 & 0.044872 \tabularnewline
[11,12[ & 11.5 & 1 & 0.00641 & 0.974359 & 0.00641 \tabularnewline
[12,13[ & 12.5 & 2 & 0.012821 & 0.987179 & 0.012821 \tabularnewline
[13,14[ & 13.5 & 0 & 0 & 0.987179 & 0 \tabularnewline
[14,15] & 14.5 & 2 & 0.012821 & 1 & 0.012821 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104381&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][0,1[[/C][C]0.5[/C][C]16[/C][C]0.102564[/C][C]0.102564[/C][C]0.102564[/C][/ROW]
[ROW][C][1,2[[/C][C]1.5[/C][C]5[/C][C]0.032051[/C][C]0.134615[/C][C]0.032051[/C][/ROW]
[ROW][C][2,3[[/C][C]2.5[/C][C]13[/C][C]0.083333[/C][C]0.217949[/C][C]0.083333[/C][/ROW]
[ROW][C][3,4[[/C][C]3.5[/C][C]21[/C][C]0.134615[/C][C]0.352564[/C][C]0.134615[/C][/ROW]
[ROW][C][4,5[[/C][C]4.5[/C][C]12[/C][C]0.076923[/C][C]0.429487[/C][C]0.076923[/C][/ROW]
[ROW][C][5,6[[/C][C]5.5[/C][C]20[/C][C]0.128205[/C][C]0.557692[/C][C]0.128205[/C][/ROW]
[ROW][C][6,7[[/C][C]6.5[/C][C]21[/C][C]0.134615[/C][C]0.692308[/C][C]0.134615[/C][/ROW]
[ROW][C][7,8[[/C][C]7.5[/C][C]15[/C][C]0.096154[/C][C]0.788462[/C][C]0.096154[/C][/ROW]
[ROW][C][8,9[[/C][C]8.5[/C][C]14[/C][C]0.089744[/C][C]0.878205[/C][C]0.089744[/C][/ROW]
[ROW][C][9,10[[/C][C]9.5[/C][C]7[/C][C]0.044872[/C][C]0.923077[/C][C]0.044872[/C][/ROW]
[ROW][C][10,11[[/C][C]10.5[/C][C]7[/C][C]0.044872[/C][C]0.967949[/C][C]0.044872[/C][/ROW]
[ROW][C][11,12[[/C][C]11.5[/C][C]1[/C][C]0.00641[/C][C]0.974359[/C][C]0.00641[/C][/ROW]
[ROW][C][12,13[[/C][C]12.5[/C][C]2[/C][C]0.012821[/C][C]0.987179[/C][C]0.012821[/C][/ROW]
[ROW][C][13,14[[/C][C]13.5[/C][C]0[/C][C]0[/C][C]0.987179[/C][C]0[/C][/ROW]
[ROW][C][14,15][/C][C]14.5[/C][C]2[/C][C]0.012821[/C][C]1[/C][C]0.012821[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104381&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104381&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
[0,1[0.5160.1025640.1025640.102564
[1,2[1.550.0320510.1346150.032051
[2,3[2.5130.0833330.2179490.083333
[3,4[3.5210.1346150.3525640.134615
[4,5[4.5120.0769230.4294870.076923
[5,6[5.5200.1282050.5576920.128205
[6,7[6.5210.1346150.6923080.134615
[7,8[7.5150.0961540.7884620.096154
[8,9[8.5140.0897440.8782050.089744
[9,10[9.570.0448720.9230770.044872
[10,11[10.570.0448720.9679490.044872
[11,12[11.510.006410.9743590.00641
[12,13[12.520.0128210.9871790.012821
[13,14[13.5000.9871790
[14,15]14.520.01282110.012821



Parameters (Session):
par1 = 5 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 15 ; 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')
}