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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 15 Dec 2014 12:04:17 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t141864507346r7ndo1d2k84te.htm/, Retrieved Thu, 16 May 2024 10:51:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268196, Retrieved Thu, 16 May 2024 10:51:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Bad example of Hi...] [2010-09-25 09:28:23] [b98453cac15ba1066b407e146608df68]
- RMPD  [Notched Boxplots] [] [2014-12-14 19:03:30] [bcd8153d44f369b7624d3c1b4621c4c3]
- RMPD    [Histogram] [] [2014-12-15 11:47:31] [bcd8153d44f369b7624d3c1b4621c4c3]
- R         [Histogram] [] [2014-12-15 11:51:14] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D          [Histogram] [] [2014-12-15 12:04:17] [6e98989d1e11d52934121e5a163a7817] [Current]
-    D            [Histogram] [] [2014-12-15 12:06:17] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D              [Histogram] [] [2014-12-15 12:11:40] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D                [Histogram] [] [2014-12-15 12:14:37] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D                  [Histogram] [] [2014-12-15 12:17:19] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D                    [Histogram] [] [2014-12-15 12:20:32] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D                      [Histogram] [] [2014-12-15 12:23:31] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D                        [Histogram] [] [2014-12-15 12:24:32] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D                          [Histogram] [] [2014-12-15 12:25:39] [bcd8153d44f369b7624d3c1b4621c4c3]
-    D                            [Histogram] [] [2014-12-15 12:26:25] [bcd8153d44f369b7624d3c1b4621c4c3]
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Dataseries X:
5
6
4
4
4
5
3
7
2
6
4
2
4
4
3
7
5
5
4
2
8
3
4
2
5
8
4
6
3
4
4
3
6
3
5
3
4
6
6
5
6
3
3
4
5
3
5
4
10
3
4
3
4
4
3
6
4
2
4
2
3
4
6
9
4
8
4
7
8
3
5
4
3
5
5
4
5
7
7
7
7
3
6
8
0
3
6
3
3
4
0
1
3
7
3
9
4
3
3
6
2
4
0
2
6
5
4
7
4
5
3
3
7
5
5
7
4
5
4
4
0
7
5
6
5
4
1
6
5
5
5
NA
3
5
7
5
1
5
4
5
5
5
2
4
6
5
6
7
4
2
6
5
3
4
5
4
3
5
3
4
6
3
5
6
6
3
6
6
4
4
5
6
4
4
4
4
6
8
6
4
4
9
6
4
3
4
5
4
8
5
4
5
4
2
7
2
3
7
4
7
9
7
5
4
6
3
3
5
5
7
9
5
5
1
6
5
4
2
5
3
5
4
6
7
5
5
2
3
5
2
2
5
2
3
4
8
4
2
5
4
5
8
6
9
2
3
6
2
3
1
2
1
2
5
6
2
2
4
5
2
1
1
5
0
5
3
7
6
2
5
2
2
6
3
3
1
1
3
1
4
3
2
4
3
1
3
1
9
3
4
1
4
5
3
3
2
5
2
2
5
2
5
4
4
0
0
3
1
2
2
2
1
4
5
1
4
7
1
4
3
4
4
3
4
3
4
5
2
5
7
8
4
5
1
2
0
6
1
4
4
4
3
2
1
3
6
2
1
4
4
2
0
4
5
6
2
2
4
0
5
7
6
5
1
4
3
3
7
3
3
5
3
7
3
2
6
2
3
1
3
7
3
4
1
2
2
7
1
1
4
2
3
3
3
3
2
4
5
5
2
2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268196&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]0 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=268196&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268196&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,1[0.5100.0249380.0249380.025
[1,2[1.5270.0673320.0922690.0675
[2,3[2.5510.1271820.2194510.1275
[3,4[3.5700.1745640.3940150.175
[4,5[4.5850.211970.6059850.2125
[5,6[5.5710.1770570.7830420.1775
[6,7[6.5400.0997510.8827930.1
[7,8[7.5280.0698250.9526180.07
[8,9[8.5100.0249380.9775560.025
[9,10]9.580.019950.9975060.02

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,1[ & 0.5 & 10 & 0.024938 & 0.024938 & 0.025 \tabularnewline
[1,2[ & 1.5 & 27 & 0.067332 & 0.092269 & 0.0675 \tabularnewline
[2,3[ & 2.5 & 51 & 0.127182 & 0.219451 & 0.1275 \tabularnewline
[3,4[ & 3.5 & 70 & 0.174564 & 0.394015 & 0.175 \tabularnewline
[4,5[ & 4.5 & 85 & 0.21197 & 0.605985 & 0.2125 \tabularnewline
[5,6[ & 5.5 & 71 & 0.177057 & 0.783042 & 0.1775 \tabularnewline
[6,7[ & 6.5 & 40 & 0.099751 & 0.882793 & 0.1 \tabularnewline
[7,8[ & 7.5 & 28 & 0.069825 & 0.952618 & 0.07 \tabularnewline
[8,9[ & 8.5 & 10 & 0.024938 & 0.977556 & 0.025 \tabularnewline
[9,10] & 9.5 & 8 & 0.01995 & 0.997506 & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268196&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][0,1[[/C][C]0.5[/C][C]10[/C][C]0.024938[/C][C]0.024938[/C][C]0.025[/C][/ROW]
[ROW][C][1,2[[/C][C]1.5[/C][C]27[/C][C]0.067332[/C][C]0.092269[/C][C]0.0675[/C][/ROW]
[ROW][C][2,3[[/C][C]2.5[/C][C]51[/C][C]0.127182[/C][C]0.219451[/C][C]0.1275[/C][/ROW]
[ROW][C][3,4[[/C][C]3.5[/C][C]70[/C][C]0.174564[/C][C]0.394015[/C][C]0.175[/C][/ROW]
[ROW][C][4,5[[/C][C]4.5[/C][C]85[/C][C]0.21197[/C][C]0.605985[/C][C]0.2125[/C][/ROW]
[ROW][C][5,6[[/C][C]5.5[/C][C]71[/C][C]0.177057[/C][C]0.783042[/C][C]0.1775[/C][/ROW]
[ROW][C][6,7[[/C][C]6.5[/C][C]40[/C][C]0.099751[/C][C]0.882793[/C][C]0.1[/C][/ROW]
[ROW][C][7,8[[/C][C]7.5[/C][C]28[/C][C]0.069825[/C][C]0.952618[/C][C]0.07[/C][/ROW]
[ROW][C][8,9[[/C][C]8.5[/C][C]10[/C][C]0.024938[/C][C]0.977556[/C][C]0.025[/C][/ROW]
[ROW][C][9,10][/C][C]9.5[/C][C]8[/C][C]0.01995[/C][C]0.997506[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268196&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268196&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)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,1[0.5100.0249380.0249380.025
[1,2[1.5270.0673320.0922690.0675
[2,3[2.5510.1271820.2194510.1275
[3,4[3.5700.1745640.3940150.175
[4,5[4.5850.211970.6059850.2125
[5,6[5.5710.1770570.7830420.1775
[6,7[6.5400.0997510.8827930.1
[7,8[7.5280.0698250.9526180.07
[8,9[8.5100.0249380.9775560.025
[9,10]9.580.019950.9975060.02







Summary Statistics
> summary(x)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
  0.000   3.000   4.000   4.058   5.000  10.000       1 

\begin{tabular}{lllllllll}
\hline
Summary Statistics \tabularnewline
> summary(x)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
  0.000   3.000   4.000   4.058   5.000  10.000       1 
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=268196&T=2

[TABLE]
[ROW][C]Summary Statistics[/C][/ROW]
[ROW][C]
> summary(x)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
  0.000   3.000   4.000   4.058   5.000  10.000       1 
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=268196&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268196&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary Statistics
> summary(x)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
  0.000   3.000   4.000   4.058   5.000  10.000       1 



Parameters (Session):
Parameters (R input):
par1 = 10 ; par2 = brown ; 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')
}

a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary Statistics',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('summary(x)'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')