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Author's title

Author

*Unverified author*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Tue, 12 Feb 2013 14:06:12 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Feb/12/t136069621898yv2qgv7rcx8yn.htm/, Retrieved Mon, 29 Apr 2024 06:04:39 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=206435, Retrieved Mon, 29 Apr 2024 06:04:39 +0000

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Original text written by user:

De prijs die het meeste voorkwam in de afgelopen 5jaar ligt tussen 10.4-10.6�

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

105

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Univariate Data Series] [Gemiddelde consum...] [2013-02-04 23:50:25] [812272bcf10cd97986bd11f9adf3f369]
- R PD  [Univariate Data Series] [] [2013-02-12 13:22:58] [812272bcf10cd97986bd11f9adf3f369]
- RMPD      [Histogram] [Maaltijd in resta...] [2013-02-12 19:06:12] [1f4ca98ed28755372cdf3133ccb2c2d2] [Current]

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Dataseries X:

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Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=206435&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=206435&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=206435&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[9,9.2[	9.1	6	0.083333	0.083333	0.416667
[9.2,9.4[	9.3	10	0.138889	0.222222	0.694444
[9.4,9.6[	9.5	10	0.138889	0.361111	0.694444
[9.6,9.8[	9.7	4	0.055556	0.416667	0.277778
[9.8,10[	9.9	7	0.097222	0.513889	0.486111
[10,10.2[	10.1	6	0.083333	0.597222	0.416667
[10.2,10.4[	10.3	10	0.138889	0.736111	0.694444
[10.4,10.6]	10.5	19	0.263889	1	1.319444

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[9,9.2[ & 9.1 & 6 & 0.083333 & 0.083333 & 0.416667 \tabularnewline
[9.2,9.4[ & 9.3 & 10 & 0.138889 & 0.222222 & 0.694444 \tabularnewline
[9.4,9.6[ & 9.5 & 10 & 0.138889 & 0.361111 & 0.694444 \tabularnewline
[9.6,9.8[ & 9.7 & 4 & 0.055556 & 0.416667 & 0.277778 \tabularnewline
[9.8,10[ & 9.9 & 7 & 0.097222 & 0.513889 & 0.486111 \tabularnewline
[10,10.2[ & 10.1 & 6 & 0.083333 & 0.597222 & 0.416667 \tabularnewline
[10.2,10.4[ & 10.3 & 10 & 0.138889 & 0.736111 & 0.694444 \tabularnewline
[10.4,10.6] & 10.5 & 19 & 0.263889 & 1 & 1.319444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=206435&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][9,9.2[[/C][C]9.1[/C][C]6[/C][C]0.083333[/C][C]0.083333[/C][C]0.416667[/C][/ROW]
[ROW][C][9.2,9.4[[/C][C]9.3[/C][C]10[/C][C]0.138889[/C][C]0.222222[/C][C]0.694444[/C][/ROW]
[ROW][C][9.4,9.6[[/C][C]9.5[/C][C]10[/C][C]0.138889[/C][C]0.361111[/C][C]0.694444[/C][/ROW]
[ROW][C][9.6,9.8[[/C][C]9.7[/C][C]4[/C][C]0.055556[/C][C]0.416667[/C][C]0.277778[/C][/ROW]
[ROW][C][9.8,10[[/C][C]9.9[/C][C]7[/C][C]0.097222[/C][C]0.513889[/C][C]0.486111[/C][/ROW]
[ROW][C][10,10.2[[/C][C]10.1[/C][C]6[/C][C]0.083333[/C][C]0.597222[/C][C]0.416667[/C][/ROW]
[ROW][C][10.2,10.4[[/C][C]10.3[/C][C]10[/C][C]0.138889[/C][C]0.736111[/C][C]0.694444[/C][/ROW]
[ROW][C][10.4,10.6][/C][C]10.5[/C][C]19[/C][C]0.263889[/C][C]1[/C][C]1.319444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=206435&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=206435&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)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[9,9.2[	9.1	6	0.083333	0.083333	0.416667
[9.2,9.4[	9.3	10	0.138889	0.222222	0.694444
[9.4,9.6[	9.5	10	0.138889	0.361111	0.694444
[9.6,9.8[	9.7	4	0.055556	0.416667	0.277778
[9.8,10[	9.9	7	0.097222	0.513889	0.486111
[10,10.2[	10.1	6	0.083333	0.597222	0.416667
[10.2,10.4[	10.3	10	0.138889	0.736111	0.694444
[10.4,10.6]	10.5	19	0.263889	1	1.319444

Figure 1

PNG link

Postscript link

PDF link

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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code