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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Mon, 16 Apr 2012 06:44:30 -0400

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/2012/Apr/16/t1334573115smq80pv1pvq76au.htm/, Retrieved Mon, 29 Apr 2024 02:57:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164368, Retrieved Mon, 29 Apr 2024 02:57:08 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

164

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

-       [Histogram] [] [2012-04-16 10:44:30] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 09:50:26] [2805bc4d0d3810b6cd96238758e5985d] 
-           [Recursive Partitioning (Regression Trees)] [] [2012-05-22 13:07:48] [d67971843857ce8a39847b8686da437b] 
-   P       [Recursive Partitioning (Regression Trees)] [] [2012-05-22 13:14:14] [d67971843857ce8a39847b8686da437b] 
-   P       [Recursive Partitioning (Regression Trees)] [] [2012-05-22 13:17:48] [d67971843857ce8a39847b8686da437b] 
-   P       [Recursive Partitioning (Regression Trees)] [] [2012-05-22 13:26:44] [d67971843857ce8a39847b8686da437b] 
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 10:04:56] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 10:15:09] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 10:47:41] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 10:57:12] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 11:06:10] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 11:16:54] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Recursive Partitioning (Regression Trees)] [] [2012-05-01 11:23:17] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Social Networking] [] [2012-05-01 12:43:17] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Social Networking] [] [2012-05-01 12:44:58] [2805bc4d0d3810b6cd96238758e5985d] 
- RMPD    [Social Networking] [] [2012-05-01 12:51:25] [2805bc4d0d3810b6cd96238758e5985d] 

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Histogram

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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=164368&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=164368&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164368&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 (Categorical Data)
Category	Abs. Frequency	Rel. Frequency
0	240	0.2019
1	251	0.2111
2	331	0.2784
3	367	0.3087

\begin{tabular}{lllllllll}
\hline
Frequency Table (Categorical Data) \tabularnewline
Category & Abs. Frequency & Rel. Frequency \tabularnewline
0 & 240 & 0.2019 \tabularnewline
1 & 251 & 0.2111 \tabularnewline
2 & 331 & 0.2784 \tabularnewline
3 & 367 & 0.3087 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164368&T=1

[TABLE]
[ROW][C]Frequency Table (Categorical Data)[/C][/ROW]
[ROW][C]Category[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][/ROW]
[ROW][C]0[/C][C]240[/C][C]0.2019[/C][/ROW]
[ROW][C]1[/C][C]251[/C][C]0.2111[/C][/ROW]
[ROW][C]2[/C][C]331[/C][C]0.2784[/C][/ROW]
[ROW][C]3[/C][C]367[/C][C]0.3087[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164368&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164368&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 (Categorical Data)
Category	Abs. Frequency	Rel. Frequency
0	240	0.2019
1	251	0.2111
2	331	0.2784
3	367	0.3087

Figure 1

PNG link

Postscript link

PDF link

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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code