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Author's title

Author

*Unverified author*

R Software Module

Title produced by software

Histogram

Date of computation

Thu, 26 Sep 2013 11:30:42 -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/2013/Sep/26/t1380209502tmmlsa06dxhka89.htm/, Retrieved Mon, 29 Apr 2024 13:22:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=212146, Retrieved Mon, 29 Apr 2024 13:22:01 +0000

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User-defined keywords

Estimated Impact

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

-     [Histogram] [] [2013-09-25 08:57:40] [c19d7b9cd6c492e87112b55d15521e82]
- RM      [Histogram] [] [2013-09-26 15:30:42] [d41d8cd98f00b204e9800998ecf8427e] [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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212146&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=212146&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212146&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[12,14[	13	3	0.035714	0.035714	0.017857
[14,16[	15	3	0.035714	0.071429	0.017857
[16,18[	17	9	0.107143	0.178571	0.053571
[18,20[	19	24	0.285714	0.464286	0.142857
[20,22[	21	15	0.178571	0.642857	0.089286
[22,24[	23	18	0.214286	0.857143	0.107143
[24,26[	25	9	0.107143	0.964286	0.053571
[26,28[	27	0	0	0.964286	0
[28,30]	29	3	0.035714	1	0.017857

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[12,14[ & 13 & 3 & 0.035714 & 0.035714 & 0.017857 \tabularnewline
[14,16[ & 15 & 3 & 0.035714 & 0.071429 & 0.017857 \tabularnewline
[16,18[ & 17 & 9 & 0.107143 & 0.178571 & 0.053571 \tabularnewline
[18,20[ & 19 & 24 & 0.285714 & 0.464286 & 0.142857 \tabularnewline
[20,22[ & 21 & 15 & 0.178571 & 0.642857 & 0.089286 \tabularnewline
[22,24[ & 23 & 18 & 0.214286 & 0.857143 & 0.107143 \tabularnewline
[24,26[ & 25 & 9 & 0.107143 & 0.964286 & 0.053571 \tabularnewline
[26,28[ & 27 & 0 & 0 & 0.964286 & 0 \tabularnewline
[28,30] & 29 & 3 & 0.035714 & 1 & 0.017857 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212146&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][12,14[[/C][C]13[/C][C]3[/C][C]0.035714[/C][C]0.035714[/C][C]0.017857[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]3[/C][C]0.035714[/C][C]0.071429[/C][C]0.017857[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]9[/C][C]0.107143[/C][C]0.178571[/C][C]0.053571[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]24[/C][C]0.285714[/C][C]0.464286[/C][C]0.142857[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]15[/C][C]0.178571[/C][C]0.642857[/C][C]0.089286[/C][/ROW]
[ROW][C][22,24[[/C][C]23[/C][C]18[/C][C]0.214286[/C][C]0.857143[/C][C]0.107143[/C][/ROW]
[ROW][C][24,26[[/C][C]25[/C][C]9[/C][C]0.107143[/C][C]0.964286[/C][C]0.053571[/C][/ROW]
[ROW][C][26,28[[/C][C]27[/C][C]0[/C][C]0[/C][C]0.964286[/C][C]0[/C][/ROW]
[ROW][C][28,30][/C][C]29[/C][C]3[/C][C]0.035714[/C][C]1[/C][C]0.017857[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=212146&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212146&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
[12,14[	13	3	0.035714	0.035714	0.017857
[14,16[	15	3	0.035714	0.071429	0.017857
[16,18[	17	9	0.107143	0.178571	0.053571
[18,20[	19	24	0.285714	0.464286	0.142857
[20,22[	21	15	0.178571	0.642857	0.089286
[22,24[	23	18	0.214286	0.857143	0.107143
[24,26[	25	9	0.107143	0.964286	0.053571
[26,28[	27	0	0	0.964286	0
[28,30]	29	3	0.035714	1	0.017857

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 ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;

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