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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 23 Dec 2011 04:02:43 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/23/t13246309806i33m1fdj8f2sv2.htm/, Retrieved Sun, 11 May 2025 07:31:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160209, Retrieved Sun, 11 May 2025 07:31:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMPD        [(Partial) Autocorrelation Function] [] [2011-11-25 15:10:22] [b1eb71d4db1ceb5d347df987feb4a25e]
- RMPD            [Histogram] [Paper 2] [2011-12-23 09:02:43] [8829043a11b4adcf2fcb2d15cd36bb4f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26
20
19
19
20
25
25
22
26
22
17
22
19
24
26
21
13
26
20
22
14
21
7
23
17
25
25
19
20
23
22
22
21
15
20
22
18
20
28
22
18
23
20
25
26
15
17
23
21
13
18
19
22
16
24
18
20
24
14
22
24
18
21
23
17
22
24
21
22
16
21
23
22
24
24
16
16
21
26
15
25
18
23
20
17
25
24
17
19
20
15
27
22
23
16
19
25
19
19
26
21
20
24
22
20
18
18
24
24
22
23
22
20
18
25
18
16
20
19
15
19
19
16
17
28
23
25
20
17
23
16
23
11
18
24
23
21
16
24
23
18
20
9
24
25
20
21
25
22
21
21
22
27
24
24
21
18
16
22
20
18
20

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160209&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160209&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160209&T=0

As an alternative you can also use a QR Code:  
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'Gertrude Mary Cox' @ cox.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[6,8[710.0061730.0061730.003086
[8,10[910.0061730.0123460.003086
[10,12[1110.0061730.0185190.003086
[12,14[1320.0123460.0308640.006173
[14,16[1570.043210.0740740.021605
[16,18[17180.1111110.1851850.055556
[18,20[19260.1604940.3456790.080247
[20,22[21330.2037040.5493830.101852
[22,24[23340.2098770.7592590.104938
[24,26[25280.172840.9320990.08642
[26,28]27110.06790110.033951

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[6,8[ & 7 & 1 & 0.006173 & 0.006173 & 0.003086 \tabularnewline
[8,10[ & 9 & 1 & 0.006173 & 0.012346 & 0.003086 \tabularnewline
[10,12[ & 11 & 1 & 0.006173 & 0.018519 & 0.003086 \tabularnewline
[12,14[ & 13 & 2 & 0.012346 & 0.030864 & 0.006173 \tabularnewline
[14,16[ & 15 & 7 & 0.04321 & 0.074074 & 0.021605 \tabularnewline
[16,18[ & 17 & 18 & 0.111111 & 0.185185 & 0.055556 \tabularnewline
[18,20[ & 19 & 26 & 0.160494 & 0.345679 & 0.080247 \tabularnewline
[20,22[ & 21 & 33 & 0.203704 & 0.549383 & 0.101852 \tabularnewline
[22,24[ & 23 & 34 & 0.209877 & 0.759259 & 0.104938 \tabularnewline
[24,26[ & 25 & 28 & 0.17284 & 0.932099 & 0.08642 \tabularnewline
[26,28] & 27 & 11 & 0.067901 & 1 & 0.033951 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160209&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][6,8[[/C][C]7[/C][C]1[/C][C]0.006173[/C][C]0.006173[/C][C]0.003086[/C][/ROW]
[ROW][C][8,10[[/C][C]9[/C][C]1[/C][C]0.006173[/C][C]0.012346[/C][C]0.003086[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]1[/C][C]0.006173[/C][C]0.018519[/C][C]0.003086[/C][/ROW]
[ROW][C][12,14[[/C][C]13[/C][C]2[/C][C]0.012346[/C][C]0.030864[/C][C]0.006173[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]7[/C][C]0.04321[/C][C]0.074074[/C][C]0.021605[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]18[/C][C]0.111111[/C][C]0.185185[/C][C]0.055556[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]26[/C][C]0.160494[/C][C]0.345679[/C][C]0.080247[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]33[/C][C]0.203704[/C][C]0.549383[/C][C]0.101852[/C][/ROW]
[ROW][C][22,24[[/C][C]23[/C][C]34[/C][C]0.209877[/C][C]0.759259[/C][C]0.104938[/C][/ROW]
[ROW][C][24,26[[/C][C]25[/C][C]28[/C][C]0.17284[/C][C]0.932099[/C][C]0.08642[/C][/ROW]
[ROW][C][26,28][/C][C]27[/C][C]11[/C][C]0.067901[/C][C]1[/C][C]0.033951[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160209&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160209&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[6,8[710.0061730.0061730.003086
[8,10[910.0061730.0123460.003086
[10,12[1110.0061730.0185190.003086
[12,14[1320.0123460.0308640.006173
[14,16[1570.043210.0740740.021605
[16,18[17180.1111110.1851850.055556
[18,20[19260.1604940.3456790.080247
[20,22[21330.2037040.5493830.101852
[22,24[23340.2098770.7592590.104938
[24,26[25280.172840.9320990.08642
[26,28]27110.06790110.033951


Figures (Output of Computation)

Input Parameters & R Code

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')
}