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Author

*Unverified author*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Mon, 11 Feb 2013 16:57:54 -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/11/t1360619933k302dflcynjzqwc.htm/, Retrieved Tue, 30 Apr 2024 06:42:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=206292, Retrieved Tue, 30 Apr 2024 06:42:38 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

115

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

-     [Univariate Data Series] [gemiddelde consum...] [2013-02-01 14:20:20] [35bfe82417f54a697465904b974d620c]
- RMPD    [Histogram] [joggingschoenen] [2013-02-11 21:57:54] [69bb275cfc110db963587bebba58b9f3] [Current]

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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	2 seconds
R Server	'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=206292&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=206292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=206292&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	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[84.9,85[	84.95	1	0.014925	0.014925	0.149254
[85,85.1[	85.05	0	0	0.014925	0
[85.1,85.2[	85.15	5	0.074627	0.089552	0.746269
[85.2,85.3[	85.25	0	0	0.089552	0
[85.3,85.4[	85.35	2	0.029851	0.119403	0.298507
[85.4,85.5[	85.45	0	0	0.119403	0
[85.5,85.6[	85.55	5	0.074627	0.19403	0.746269
[85.6,85.7[	85.65	6	0.089552	0.283582	0.895522
[85.7,85.8[	85.75	1	0.014925	0.298507	0.149254
[85.8,85.9[	85.85	1	0.014925	0.313433	0.149254
[85.9,86[	85.95	1	0.014925	0.328358	0.149254
[86,86.1[	86.05	1	0.014925	0.343284	0.149254
[86.1,86.2[	86.15	1	0.014925	0.358209	0.149254
[86.2,86.3[	86.25	3	0.044776	0.402985	0.447761
[86.3,86.4[	86.35	6	0.089552	0.492537	0.895522
[86.4,86.5[	86.45	6	0.089552	0.58209	0.895522
[86.5,86.6[	86.55	1	0.014925	0.597015	0.149254
[86.6,86.7[	86.65	4	0.059701	0.656716	0.597015
[86.7,86.8[	86.75	3	0.044776	0.701493	0.447761
[86.8,86.9[	86.85	5	0.074627	0.776119	0.746269
[86.9,87[	86.95	7	0.104478	0.880597	1.044776
[87,87.1[	87.05	3	0.044776	0.925373	0.447761
[87.1,87.2[	87.15	2	0.029851	0.955224	0.298507
[87.2,87.3]	87.25	3	0.044776	1	0.447761

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[84.9,85[ & 84.95 & 1 & 0.014925 & 0.014925 & 0.149254 \tabularnewline
[85,85.1[ & 85.05 & 0 & 0 & 0.014925 & 0 \tabularnewline
[85.1,85.2[ & 85.15 & 5 & 0.074627 & 0.089552 & 0.746269 \tabularnewline
[85.2,85.3[ & 85.25 & 0 & 0 & 0.089552 & 0 \tabularnewline
[85.3,85.4[ & 85.35 & 2 & 0.029851 & 0.119403 & 0.298507 \tabularnewline
[85.4,85.5[ & 85.45 & 0 & 0 & 0.119403 & 0 \tabularnewline
[85.5,85.6[ & 85.55 & 5 & 0.074627 & 0.19403 & 0.746269 \tabularnewline
[85.6,85.7[ & 85.65 & 6 & 0.089552 & 0.283582 & 0.895522 \tabularnewline
[85.7,85.8[ & 85.75 & 1 & 0.014925 & 0.298507 & 0.149254 \tabularnewline
[85.8,85.9[ & 85.85 & 1 & 0.014925 & 0.313433 & 0.149254 \tabularnewline
[85.9,86[ & 85.95 & 1 & 0.014925 & 0.328358 & 0.149254 \tabularnewline
[86,86.1[ & 86.05 & 1 & 0.014925 & 0.343284 & 0.149254 \tabularnewline
[86.1,86.2[ & 86.15 & 1 & 0.014925 & 0.358209 & 0.149254 \tabularnewline
[86.2,86.3[ & 86.25 & 3 & 0.044776 & 0.402985 & 0.447761 \tabularnewline
[86.3,86.4[ & 86.35 & 6 & 0.089552 & 0.492537 & 0.895522 \tabularnewline
[86.4,86.5[ & 86.45 & 6 & 0.089552 & 0.58209 & 0.895522 \tabularnewline
[86.5,86.6[ & 86.55 & 1 & 0.014925 & 0.597015 & 0.149254 \tabularnewline
[86.6,86.7[ & 86.65 & 4 & 0.059701 & 0.656716 & 0.597015 \tabularnewline
[86.7,86.8[ & 86.75 & 3 & 0.044776 & 0.701493 & 0.447761 \tabularnewline
[86.8,86.9[ & 86.85 & 5 & 0.074627 & 0.776119 & 0.746269 \tabularnewline
[86.9,87[ & 86.95 & 7 & 0.104478 & 0.880597 & 1.044776 \tabularnewline
[87,87.1[ & 87.05 & 3 & 0.044776 & 0.925373 & 0.447761 \tabularnewline
[87.1,87.2[ & 87.15 & 2 & 0.029851 & 0.955224 & 0.298507 \tabularnewline
[87.2,87.3] & 87.25 & 3 & 0.044776 & 1 & 0.447761 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=206292&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][84.9,85[[/C][C]84.95[/C][C]1[/C][C]0.014925[/C][C]0.014925[/C][C]0.149254[/C][/ROW]
[ROW][C][85,85.1[[/C][C]85.05[/C][C]0[/C][C]0[/C][C]0.014925[/C][C]0[/C][/ROW]
[ROW][C][85.1,85.2[[/C][C]85.15[/C][C]5[/C][C]0.074627[/C][C]0.089552[/C][C]0.746269[/C][/ROW]
[ROW][C][85.2,85.3[[/C][C]85.25[/C][C]0[/C][C]0[/C][C]0.089552[/C][C]0[/C][/ROW]
[ROW][C][85.3,85.4[[/C][C]85.35[/C][C]2[/C][C]0.029851[/C][C]0.119403[/C][C]0.298507[/C][/ROW]
[ROW][C][85.4,85.5[[/C][C]85.45[/C][C]0[/C][C]0[/C][C]0.119403[/C][C]0[/C][/ROW]
[ROW][C][85.5,85.6[[/C][C]85.55[/C][C]5[/C][C]0.074627[/C][C]0.19403[/C][C]0.746269[/C][/ROW]
[ROW][C][85.6,85.7[[/C][C]85.65[/C][C]6[/C][C]0.089552[/C][C]0.283582[/C][C]0.895522[/C][/ROW]
[ROW][C][85.7,85.8[[/C][C]85.75[/C][C]1[/C][C]0.014925[/C][C]0.298507[/C][C]0.149254[/C][/ROW]
[ROW][C][85.8,85.9[[/C][C]85.85[/C][C]1[/C][C]0.014925[/C][C]0.313433[/C][C]0.149254[/C][/ROW]
[ROW][C][85.9,86[[/C][C]85.95[/C][C]1[/C][C]0.014925[/C][C]0.328358[/C][C]0.149254[/C][/ROW]
[ROW][C][86,86.1[[/C][C]86.05[/C][C]1[/C][C]0.014925[/C][C]0.343284[/C][C]0.149254[/C][/ROW]
[ROW][C][86.1,86.2[[/C][C]86.15[/C][C]1[/C][C]0.014925[/C][C]0.358209[/C][C]0.149254[/C][/ROW]
[ROW][C][86.2,86.3[[/C][C]86.25[/C][C]3[/C][C]0.044776[/C][C]0.402985[/C][C]0.447761[/C][/ROW]
[ROW][C][86.3,86.4[[/C][C]86.35[/C][C]6[/C][C]0.089552[/C][C]0.492537[/C][C]0.895522[/C][/ROW]
[ROW][C][86.4,86.5[[/C][C]86.45[/C][C]6[/C][C]0.089552[/C][C]0.58209[/C][C]0.895522[/C][/ROW]
[ROW][C][86.5,86.6[[/C][C]86.55[/C][C]1[/C][C]0.014925[/C][C]0.597015[/C][C]0.149254[/C][/ROW]
[ROW][C][86.6,86.7[[/C][C]86.65[/C][C]4[/C][C]0.059701[/C][C]0.656716[/C][C]0.597015[/C][/ROW]
[ROW][C][86.7,86.8[[/C][C]86.75[/C][C]3[/C][C]0.044776[/C][C]0.701493[/C][C]0.447761[/C][/ROW]
[ROW][C][86.8,86.9[[/C][C]86.85[/C][C]5[/C][C]0.074627[/C][C]0.776119[/C][C]0.746269[/C][/ROW]
[ROW][C][86.9,87[[/C][C]86.95[/C][C]7[/C][C]0.104478[/C][C]0.880597[/C][C]1.044776[/C][/ROW]
[ROW][C][87,87.1[[/C][C]87.05[/C][C]3[/C][C]0.044776[/C][C]0.925373[/C][C]0.447761[/C][/ROW]
[ROW][C][87.1,87.2[[/C][C]87.15[/C][C]2[/C][C]0.029851[/C][C]0.955224[/C][C]0.298507[/C][/ROW]
[ROW][C][87.2,87.3][/C][C]87.25[/C][C]3[/C][C]0.044776[/C][C]1[/C][C]0.447761[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=206292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=206292&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
[84.9,85[	84.95	1	0.014925	0.014925	0.149254
[85,85.1[	85.05	0	0	0.014925	0
[85.1,85.2[	85.15	5	0.074627	0.089552	0.746269
[85.2,85.3[	85.25	0	0	0.089552	0
[85.3,85.4[	85.35	2	0.029851	0.119403	0.298507
[85.4,85.5[	85.45	0	0	0.119403	0
[85.5,85.6[	85.55	5	0.074627	0.19403	0.746269
[85.6,85.7[	85.65	6	0.089552	0.283582	0.895522
[85.7,85.8[	85.75	1	0.014925	0.298507	0.149254
[85.8,85.9[	85.85	1	0.014925	0.313433	0.149254
[85.9,86[	85.95	1	0.014925	0.328358	0.149254
[86,86.1[	86.05	1	0.014925	0.343284	0.149254
[86.1,86.2[	86.15	1	0.014925	0.358209	0.149254
[86.2,86.3[	86.25	3	0.044776	0.402985	0.447761
[86.3,86.4[	86.35	6	0.089552	0.492537	0.895522
[86.4,86.5[	86.45	6	0.089552	0.58209	0.895522
[86.5,86.6[	86.55	1	0.014925	0.597015	0.149254
[86.6,86.7[	86.65	4	0.059701	0.656716	0.597015
[86.7,86.8[	86.75	3	0.044776	0.701493	0.447761
[86.8,86.9[	86.85	5	0.074627	0.776119	0.746269
[86.9,87[	86.95	7	0.104478	0.880597	1.044776
[87,87.1[	87.05	3	0.044776	0.925373	0.447761
[87.1,87.2[	87.15	2	0.029851	0.955224	0.298507
[87.2,87.3]	87.25	3	0.044776	1	0.447761

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = gemiddelde consumptieprijs van joggingschoenen ; par2 = Belgostart ; par3 = gemiddelde consumptieprijs van joggingschoenen ; par4 = 12 ;

Parameters (R input):

par1 = 17 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

R code (references can be found in the software module):

par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '5'
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