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Author's title

Author

*Unverified author*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Mon, 01 Oct 2012 03:19:28 -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/Oct/01/t1349075982f6p5cmbshfqgb7l.htm/, Retrieved Thu, 02 May 2024 14:45:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=170632, Retrieved Thu, 02 May 2024 14:45:42 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

112

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

-     [Histogram] [] [2012-09-23 14:28:53] [73ff502f5cc0e8f9d4cad04b672b43dc]
- R P   [Histogram] [] [2012-10-01 07:15:21] [74be16979710d4c4e7c6647856088456]
-   P       [Histogram] [] [2012-10-01 07:19:28] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Histogram

Boxplots

1.6
2
2.6
3
2.6
2.9
2.5
2.4
1.5
1.1
0.6
0.9
1.1
1.5
1.7
1.2
0.4
-0.7
-1.4
-1.6
-1.2
-0.4
-0.2
-0.3
-0.5
0
-0.5
0.2
0.7
1.6
2.6
3.3
3.3
3.2
3.5
3.9
4.5
4.6
6.6
7.1
8.9
8.8
8.5
7.6
7.5
7.5
6.1
6.3
8.4
7.1
5.6
4.2
2.1
1.2
0.9
1.4
1.7
1.7
1.9
1.3
-0.7
0.3
0.8
0.9
1.1
2.5
2.7
3.3
4.2
3.8
3.8
3.2
2.9
1.9
1.7
1.6
1.7
1.2
0.7
-0.2
-1.5
-1.2
-1
0
-0.6
0.7
1.3
0.8
1
0.5
0.3
1
1
1.1
1.5
1.5
2
1.7
0.6
1.2
1.5
2.1
3.2
3.9
4.6
4.2
4.4
3.7
3.7
2.8
2.9
3.9
3.1
3
2.8
2.4
2.1
3.1
3
3.1
3.3
3.3
3.8
3.1
3.9
4
4.4
3.7
3.6
3.4
2.8
2.8
2.6
3.3
2.4
1.6
0.7
0
-1.1
-1.2
-1.3
-1.6
-1.3
-1.6
-1.1
-1
0.3
1.2
0.7
1.1
2.1
2.5
2.3
2.3
2.6
3.2
2.2
2.7
2.2
1.4
2.4
2
1.3
1.1
1.4
1.8
1.9
1.6

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=170632&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=170632&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=170632&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
[-2,-1.5[	-1.75	3	0.017857	0.017857	0.035714
[-1.5,-1[	-1.25	9	0.053571	0.071429	0.107143
[-1,-0.5[	-0.75	5	0.029762	0.10119	0.059524
[-0.5,0[	-0.25	6	0.035714	0.136905	0.071429
[0,0.5[	0.25	8	0.047619	0.184524	0.095238
[0.5,1[	0.75	13	0.077381	0.261905	0.154762
[1,1.5[	1.25	20	0.119048	0.380952	0.238095
[1.5,2[	1.75	20	0.119048	0.5	0.238095
[2,2.5[	2.25	15	0.089286	0.589286	0.178571
[2.5,3[	2.75	17	0.10119	0.690476	0.202381
[3,3.5[	3.25	18	0.107143	0.797619	0.214286
[3.5,4[	3.75	12	0.071429	0.869048	0.142857
[4,4.5[	4.25	6	0.035714	0.904762	0.071429
[4.5,5[	4.75	3	0.017857	0.922619	0.035714
[5,5.5[	5.25	0	0	0.922619	0
[5.5,6[	5.75	1	0.005952	0.928571	0.011905
[6,6.5[	6.25	2	0.011905	0.940476	0.02381
[6.5,7[	6.75	1	0.005952	0.946429	0.011905
[7,7.5[	7.25	2	0.011905	0.958333	0.02381
[7.5,8[	7.75	3	0.017857	0.97619	0.035714
[8,8.5[	8.25	1	0.005952	0.982143	0.011905
[8.5,9]	8.75	3	0.017857	1	0.035714

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[-2,-1.5[ & -1.75 & 3 & 0.017857 & 0.017857 & 0.035714 \tabularnewline
[-1.5,-1[ & -1.25 & 9 & 0.053571 & 0.071429 & 0.107143 \tabularnewline
[-1,-0.5[ & -0.75 & 5 & 0.029762 & 0.10119 & 0.059524 \tabularnewline
[-0.5,0[ & -0.25 & 6 & 0.035714 & 0.136905 & 0.071429 \tabularnewline
[0,0.5[ & 0.25 & 8 & 0.047619 & 0.184524 & 0.095238 \tabularnewline
[0.5,1[ & 0.75 & 13 & 0.077381 & 0.261905 & 0.154762 \tabularnewline
[1,1.5[ & 1.25 & 20 & 0.119048 & 0.380952 & 0.238095 \tabularnewline
[1.5,2[ & 1.75 & 20 & 0.119048 & 0.5 & 0.238095 \tabularnewline
[2,2.5[ & 2.25 & 15 & 0.089286 & 0.589286 & 0.178571 \tabularnewline
[2.5,3[ & 2.75 & 17 & 0.10119 & 0.690476 & 0.202381 \tabularnewline
[3,3.5[ & 3.25 & 18 & 0.107143 & 0.797619 & 0.214286 \tabularnewline
[3.5,4[ & 3.75 & 12 & 0.071429 & 0.869048 & 0.142857 \tabularnewline
[4,4.5[ & 4.25 & 6 & 0.035714 & 0.904762 & 0.071429 \tabularnewline
[4.5,5[ & 4.75 & 3 & 0.017857 & 0.922619 & 0.035714 \tabularnewline
[5,5.5[ & 5.25 & 0 & 0 & 0.922619 & 0 \tabularnewline
[5.5,6[ & 5.75 & 1 & 0.005952 & 0.928571 & 0.011905 \tabularnewline
[6,6.5[ & 6.25 & 2 & 0.011905 & 0.940476 & 0.02381 \tabularnewline
[6.5,7[ & 6.75 & 1 & 0.005952 & 0.946429 & 0.011905 \tabularnewline
[7,7.5[ & 7.25 & 2 & 0.011905 & 0.958333 & 0.02381 \tabularnewline
[7.5,8[ & 7.75 & 3 & 0.017857 & 0.97619 & 0.035714 \tabularnewline
[8,8.5[ & 8.25 & 1 & 0.005952 & 0.982143 & 0.011905 \tabularnewline
[8.5,9] & 8.75 & 3 & 0.017857 & 1 & 0.035714 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=170632&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][-2,-1.5[[/C][C]-1.75[/C][C]3[/C][C]0.017857[/C][C]0.017857[/C][C]0.035714[/C][/ROW]
[ROW][C][-1.5,-1[[/C][C]-1.25[/C][C]9[/C][C]0.053571[/C][C]0.071429[/C][C]0.107143[/C][/ROW]
[ROW][C][-1,-0.5[[/C][C]-0.75[/C][C]5[/C][C]0.029762[/C][C]0.10119[/C][C]0.059524[/C][/ROW]
[ROW][C][-0.5,0[[/C][C]-0.25[/C][C]6[/C][C]0.035714[/C][C]0.136905[/C][C]0.071429[/C][/ROW]
[ROW][C][0,0.5[[/C][C]0.25[/C][C]8[/C][C]0.047619[/C][C]0.184524[/C][C]0.095238[/C][/ROW]
[ROW][C][0.5,1[[/C][C]0.75[/C][C]13[/C][C]0.077381[/C][C]0.261905[/C][C]0.154762[/C][/ROW]
[ROW][C][1,1.5[[/C][C]1.25[/C][C]20[/C][C]0.119048[/C][C]0.380952[/C][C]0.238095[/C][/ROW]
[ROW][C][1.5,2[[/C][C]1.75[/C][C]20[/C][C]0.119048[/C][C]0.5[/C][C]0.238095[/C][/ROW]
[ROW][C][2,2.5[[/C][C]2.25[/C][C]15[/C][C]0.089286[/C][C]0.589286[/C][C]0.178571[/C][/ROW]
[ROW][C][2.5,3[[/C][C]2.75[/C][C]17[/C][C]0.10119[/C][C]0.690476[/C][C]0.202381[/C][/ROW]
[ROW][C][3,3.5[[/C][C]3.25[/C][C]18[/C][C]0.107143[/C][C]0.797619[/C][C]0.214286[/C][/ROW]
[ROW][C][3.5,4[[/C][C]3.75[/C][C]12[/C][C]0.071429[/C][C]0.869048[/C][C]0.142857[/C][/ROW]
[ROW][C][4,4.5[[/C][C]4.25[/C][C]6[/C][C]0.035714[/C][C]0.904762[/C][C]0.071429[/C][/ROW]
[ROW][C][4.5,5[[/C][C]4.75[/C][C]3[/C][C]0.017857[/C][C]0.922619[/C][C]0.035714[/C][/ROW]
[ROW][C][5,5.5[[/C][C]5.25[/C][C]0[/C][C]0[/C][C]0.922619[/C][C]0[/C][/ROW]
[ROW][C][5.5,6[[/C][C]5.75[/C][C]1[/C][C]0.005952[/C][C]0.928571[/C][C]0.011905[/C][/ROW]
[ROW][C][6,6.5[[/C][C]6.25[/C][C]2[/C][C]0.011905[/C][C]0.940476[/C][C]0.02381[/C][/ROW]
[ROW][C][6.5,7[[/C][C]6.75[/C][C]1[/C][C]0.005952[/C][C]0.946429[/C][C]0.011905[/C][/ROW]
[ROW][C][7,7.5[[/C][C]7.25[/C][C]2[/C][C]0.011905[/C][C]0.958333[/C][C]0.02381[/C][/ROW]
[ROW][C][7.5,8[[/C][C]7.75[/C][C]3[/C][C]0.017857[/C][C]0.97619[/C][C]0.035714[/C][/ROW]
[ROW][C][8,8.5[[/C][C]8.25[/C][C]1[/C][C]0.005952[/C][C]0.982143[/C][C]0.011905[/C][/ROW]
[ROW][C][8.5,9][/C][C]8.75[/C][C]3[/C][C]0.017857[/C][C]1[/C][C]0.035714[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=170632&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=170632&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
[-2,-1.5[	-1.75	3	0.017857	0.017857	0.035714
[-1.5,-1[	-1.25	9	0.053571	0.071429	0.107143
[-1,-0.5[	-0.75	5	0.029762	0.10119	0.059524
[-0.5,0[	-0.25	6	0.035714	0.136905	0.071429
[0,0.5[	0.25	8	0.047619	0.184524	0.095238
[0.5,1[	0.75	13	0.077381	0.261905	0.154762
[1,1.5[	1.25	20	0.119048	0.380952	0.238095
[1.5,2[	1.75	20	0.119048	0.5	0.238095
[2,2.5[	2.25	15	0.089286	0.589286	0.178571
[2.5,3[	2.75	17	0.10119	0.690476	0.202381
[3,3.5[	3.25	18	0.107143	0.797619	0.214286
[3.5,4[	3.75	12	0.071429	0.869048	0.142857
[4,4.5[	4.25	6	0.035714	0.904762	0.071429
[4.5,5[	4.75	3	0.017857	0.922619	0.035714
[5,5.5[	5.25	0	0	0.922619	0
[5.5,6[	5.75	1	0.005952	0.928571	0.011905
[6,6.5[	6.25	2	0.011905	0.940476	0.02381
[6.5,7[	6.75	1	0.005952	0.946429	0.011905
[7,7.5[	7.25	2	0.011905	0.958333	0.02381
[7.5,8[	7.75	3	0.017857	0.97619	0.035714
[8,8.5[	8.25	1	0.005952	0.982143	0.011905
[8.5,9]	8.75	3	0.017857	1	0.035714

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 30 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

Parameters (R input):

par1 = 30 ; 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