Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

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

Fri, 30 Nov 2012 08:03:41 -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/2012/Nov/30/t1354280636ep8z0vlane2fn20.htm/, Retrieved Fri, 03 May 2024 18:41:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195009, Retrieved Fri, 03 May 2024 18:41:43 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-     [Boxplot and Trimmed Means] [Reddy Moores Boxp...] [2010-10-12 16:37:57] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P   [Boxplot and Trimmed Means] [Reddy-Moores Plac...] [2010-10-13 09:46:26] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD    [Notched Boxplots] [] [2010-10-15 11:13:23] [b98453cac15ba1066b407e146608df68]
- RMPD        [Histogram] [] [2012-11-30 13:03:41] [564f08b1e01e129faa0d56ace254d273] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

26
20
19
NA
20
25
NA
22
26
22
NA
NA
19
24
26
NA
13
NA
NA
22
NA
21
7
NA
17
25
25
19
NA
23
NA
22
21
NA
NA
NA
18
NA
NA
22
18
23
20
NA
NA
15
NA
NA
21
NA
18
19
22
16
NA
18
20
24
NA
NA
24
18
21
NA
17
NA
NA
NA
22
16
21
NA
NA
24
24
16
16
NA
NA
NA
NA
18
NA
20
NA
NA
24
17
19
20
15
NA
22
23
16
19
NA
19
NA
NA
21
NA
24
22
NA
18
NA
24
24
22
23
22
20
18
25
NA
16
20
NA
15
19
19
16
17
28
NA
25
20
NA
NA
16
NA
NA
NA
NA
23
21
NA
NA
23
18
20
9
NA
25
20
NA
NA
NA
NA
21
22
27
NA
NA
NA
18
16
22
20
NA
20

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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195009&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195009&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195009&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	'Gwilym Jenkins' @ jenkins.wessa.net

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[6,8[	7	1	0.006173	0.006173	0.005102
[8,10[	9	1	0.006173	0.012346	0.005102
[10,12[	11	0	0	0.012346	0
[12,14[	13	1	0.006173	0.018519	0.005102
[14,16[	15	3	0.018519	0.037037	0.015306
[16,18[	17	13	0.080247	0.117284	0.066327
[18,20[	19	19	0.117284	0.234568	0.096939
[20,22[	21	21	0.12963	0.364198	0.107143
[22,24[	23	19	0.117284	0.481481	0.096939
[24,26[	25	15	0.092593	0.574074	0.076531
[26,28]	27	5	0.030864	0.604938	0.02551

\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 & 0.005102 \tabularnewline
[8,10[ & 9 & 1 & 0.006173 & 0.012346 & 0.005102 \tabularnewline
[10,12[ & 11 & 0 & 0 & 0.012346 & 0 \tabularnewline
[12,14[ & 13 & 1 & 0.006173 & 0.018519 & 0.005102 \tabularnewline
[14,16[ & 15 & 3 & 0.018519 & 0.037037 & 0.015306 \tabularnewline
[16,18[ & 17 & 13 & 0.080247 & 0.117284 & 0.066327 \tabularnewline
[18,20[ & 19 & 19 & 0.117284 & 0.234568 & 0.096939 \tabularnewline
[20,22[ & 21 & 21 & 0.12963 & 0.364198 & 0.107143 \tabularnewline
[22,24[ & 23 & 19 & 0.117284 & 0.481481 & 0.096939 \tabularnewline
[24,26[ & 25 & 15 & 0.092593 & 0.574074 & 0.076531 \tabularnewline
[26,28] & 27 & 5 & 0.030864 & 0.604938 & 0.02551 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195009&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]0.005102[/C][/ROW]
[ROW][C][8,10[[/C][C]9[/C][C]1[/C][C]0.006173[/C][C]0.012346[/C][C]0.005102[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]0[/C][C]0[/C][C]0.012346[/C][C]0[/C][/ROW]
[ROW][C][12,14[[/C][C]13[/C][C]1[/C][C]0.006173[/C][C]0.018519[/C][C]0.005102[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]3[/C][C]0.018519[/C][C]0.037037[/C][C]0.015306[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]13[/C][C]0.080247[/C][C]0.117284[/C][C]0.066327[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]19[/C][C]0.117284[/C][C]0.234568[/C][C]0.096939[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]21[/C][C]0.12963[/C][C]0.364198[/C][C]0.107143[/C][/ROW]
[ROW][C][22,24[[/C][C]23[/C][C]19[/C][C]0.117284[/C][C]0.481481[/C][C]0.096939[/C][/ROW]
[ROW][C][24,26[[/C][C]25[/C][C]15[/C][C]0.092593[/C][C]0.574074[/C][C]0.076531[/C][/ROW]
[ROW][C][26,28][/C][C]27[/C][C]5[/C][C]0.030864[/C][C]0.604938[/C][C]0.02551[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195009&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195009&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
[6,8[	7	1	0.006173	0.006173	0.005102
[8,10[	9	1	0.006173	0.012346	0.005102
[10,12[	11	0	0	0.012346	0
[12,14[	13	1	0.006173	0.018519	0.005102
[14,16[	15	3	0.018519	0.037037	0.015306
[16,18[	17	13	0.080247	0.117284	0.066327
[18,20[	19	19	0.117284	0.234568	0.096939
[20,22[	21	21	0.12963	0.364198	0.107143
[22,24[	23	19	0.117284	0.481481	0.096939
[24,26[	25	15	0.092593	0.574074	0.076531
[26,28]	27	5	0.030864	0.604938	0.02551

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