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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 computationWed, 05 Dec 2012 05:21:01 -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/2012/Dec/05/t13547028960i01pdr7r04gpjg.htm/, Retrieved Fri, 01 May 2026 05:41:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196760, Retrieved Fri, 01 May 2026 05:41:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact361

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Paper histogram (1)] [2012-12-05 10:21:01] [d0e911d4b52239734cc89860ccddde4d] [Current]
- R P     [Histogram] [g] [2012-12-05 10:28:32] [596b77fae3c3637cb35f2a3968c5e5d1]
- R P       [Histogram] [histogram depress...] [2012-12-05 10:31:04] [596b77fae3c3637cb35f2a3968c5e5d1]
- RMP       [Skewness and Kurtosis Test] [skweness & kurtos...] [2012-12-05 11:01:15] [596b77fae3c3637cb35f2a3968c5e5d1]
- RMP       [Mean versus Median] [berekening mediaa...] [2012-12-05 11:21:28] [596b77fae3c3637cb35f2a3968c5e5d1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12
11
14
12
21
12
22
11
10
13
10
8
15
14
10
14
14
11
10
13
7
14
12
14
11
9
11
15
14
13
9
15
10
11
13
8
20
12
10
10
9
14
8
14
11
13
9
11
15
11
10
14
18
14
11
12
13
9
10
15
20
12
12
14
13
11
17
12
13
14
13
15
13
10
11
19
13
17
13
9
11
10
9
12
12
13
13
12
15
22
13
15
13
15
10
11
16
11
11
10
10
16
12
11
16
19
11
16
15
24
14
15
11
15
12
10
14
13
9
15
15
14
11
8
11
11
8
10
11
13
11
20
10
15
12
14
23
14
16
11
12
10
14
12
12
11
12
13
11
19
12
17
9
12
19
18
15
14
11
9
18
16

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=196760&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=196760&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196760&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[9150.0925930.0987650.046296
[10,12[11460.2839510.3827160.141975
[12,14[13400.2469140.629630.123457
[14,16[15360.2222220.8518520.111111
[16,18[1790.0555560.9074070.027778
[18,20[1970.043210.9506170.021605
[20,22[2140.0246910.9753090.012346
[22,24]2340.02469110.012346

\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 & 15 & 0.092593 & 0.098765 & 0.046296 \tabularnewline
[10,12[ & 11 & 46 & 0.283951 & 0.382716 & 0.141975 \tabularnewline
[12,14[ & 13 & 40 & 0.246914 & 0.62963 & 0.123457 \tabularnewline
[14,16[ & 15 & 36 & 0.222222 & 0.851852 & 0.111111 \tabularnewline
[16,18[ & 17 & 9 & 0.055556 & 0.907407 & 0.027778 \tabularnewline
[18,20[ & 19 & 7 & 0.04321 & 0.950617 & 0.021605 \tabularnewline
[20,22[ & 21 & 4 & 0.024691 & 0.975309 & 0.012346 \tabularnewline
[22,24] & 23 & 4 & 0.024691 & 1 & 0.012346 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196760&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]15[/C][C]0.092593[/C][C]0.098765[/C][C]0.046296[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]46[/C][C]0.283951[/C][C]0.382716[/C][C]0.141975[/C][/ROW]
[ROW][C][12,14[[/C][C]13[/C][C]40[/C][C]0.246914[/C][C]0.62963[/C][C]0.123457[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]36[/C][C]0.222222[/C][C]0.851852[/C][C]0.111111[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]9[/C][C]0.055556[/C][C]0.907407[/C][C]0.027778[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]7[/C][C]0.04321[/C][C]0.950617[/C][C]0.021605[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]4[/C][C]0.024691[/C][C]0.975309[/C][C]0.012346[/C][/ROW]
[ROW][C][22,24][/C][C]23[/C][C]4[/C][C]0.024691[/C][C]1[/C][C]0.012346[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196760&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196760&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[9150.0925930.0987650.046296
[10,12[11460.2839510.3827160.141975
[12,14[13400.2469140.629630.123457
[14,16[15360.2222220.8518520.111111
[16,18[1790.0555560.9074070.027778
[18,20[1970.043210.9506170.021605
[20,22[2140.0246910.9753090.012346
[22,24]2340.02469110.012346


Figures (Output of Computation)

Input Parameters & R Code

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