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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 computationWed, 28 Nov 2012 08:29:17 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/28/t1354109384k5la6ha9xzxqa8n.htm/, Retrieved Mon, 29 May 2023 18:40:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194132, Retrieved Mon, 29 May 2023 18:40:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [HPC Retail Sales] [2008-03-02 16:19:32] [74be16979710d4c4e7c6647856088456]
- RM D  [Classical Decomposition] [Classical decompo...] [2012-11-10 10:49:39] [2c4ddb4bf62114b8025bb962e2c7a2b5]
- RMPD      [Histogram] [Histogram happiness] [2012-11-28 13:29:17] [b4b733de199089e913cc2b6ea19b06b9] [Current]
- RMP         [Mean versus Median] [mean-median] [2012-11-28 14:02:18] [2c4ddb4bf62114b8025bb962e2c7a2b5]
- RMP         [Stem-and-leaf Plot] [stem-and-leaf plot] [2012-11-28 14:22:07] [2c4ddb4bf62114b8025bb962e2c7a2b5]
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Dataseries X:
14
18
11
12
16
18
14
14
15
15
17
19
10
16
18
14
14
17
14
16
18
11
14
12
17
9
16
14
15
11
16
13
17
15
14
16
9
15
17
13
15
16
16
12
12
11
15
15
17
13
16
14
11
12
12
15
16
15
12
12
8
13
11
14
15
10
11
12
15
15
14
16
15
15
13
12
17
13
15
13
15
16
15
16
15
14
15
14
13
7
17
13
15
14
13
16
12
14
17
15
17
12
16
11
15
9
16
15
10
10
15
11
13
14
18
16
14
14
14
14
12
14
15
15
15
13
17
17
19
15
13
9
15
15
15
16
11
14
11
15
13
15
16
14
15
16
16
11
12
9
16
13
16
12
9
13
13
14
19
13
12
13




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194132&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194132&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194132&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[7,8[7.510.0061730.0061730.006173
[8,9[8.510.0061730.0123460.006173
[9,10[9.560.0370370.0493830.037037
[10,11[10.540.0246910.0740740.024691
[11,12[11.5120.0740740.1481480.074074
[12,13[12.5160.0987650.2469140.098765
[13,14[13.5190.1172840.3641980.117284
[14,15[14.5250.1543210.5185190.154321
[15,16[15.5350.2160490.7345680.216049
[16,17[16.5230.1419750.8765430.141975
[17,18[17.5120.0740740.9506170.074074
[18,19]18.580.04938310.049383

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[7,8[ & 7.5 & 1 & 0.006173 & 0.006173 & 0.006173 \tabularnewline
[8,9[ & 8.5 & 1 & 0.006173 & 0.012346 & 0.006173 \tabularnewline
[9,10[ & 9.5 & 6 & 0.037037 & 0.049383 & 0.037037 \tabularnewline
[10,11[ & 10.5 & 4 & 0.024691 & 0.074074 & 0.024691 \tabularnewline
[11,12[ & 11.5 & 12 & 0.074074 & 0.148148 & 0.074074 \tabularnewline
[12,13[ & 12.5 & 16 & 0.098765 & 0.246914 & 0.098765 \tabularnewline
[13,14[ & 13.5 & 19 & 0.117284 & 0.364198 & 0.117284 \tabularnewline
[14,15[ & 14.5 & 25 & 0.154321 & 0.518519 & 0.154321 \tabularnewline
[15,16[ & 15.5 & 35 & 0.216049 & 0.734568 & 0.216049 \tabularnewline
[16,17[ & 16.5 & 23 & 0.141975 & 0.876543 & 0.141975 \tabularnewline
[17,18[ & 17.5 & 12 & 0.074074 & 0.950617 & 0.074074 \tabularnewline
[18,19] & 18.5 & 8 & 0.049383 & 1 & 0.049383 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194132&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][7,8[[/C][C]7.5[/C][C]1[/C][C]0.006173[/C][C]0.006173[/C][C]0.006173[/C][/ROW]
[ROW][C][8,9[[/C][C]8.5[/C][C]1[/C][C]0.006173[/C][C]0.012346[/C][C]0.006173[/C][/ROW]
[ROW][C][9,10[[/C][C]9.5[/C][C]6[/C][C]0.037037[/C][C]0.049383[/C][C]0.037037[/C][/ROW]
[ROW][C][10,11[[/C][C]10.5[/C][C]4[/C][C]0.024691[/C][C]0.074074[/C][C]0.024691[/C][/ROW]
[ROW][C][11,12[[/C][C]11.5[/C][C]12[/C][C]0.074074[/C][C]0.148148[/C][C]0.074074[/C][/ROW]
[ROW][C][12,13[[/C][C]12.5[/C][C]16[/C][C]0.098765[/C][C]0.246914[/C][C]0.098765[/C][/ROW]
[ROW][C][13,14[[/C][C]13.5[/C][C]19[/C][C]0.117284[/C][C]0.364198[/C][C]0.117284[/C][/ROW]
[ROW][C][14,15[[/C][C]14.5[/C][C]25[/C][C]0.154321[/C][C]0.518519[/C][C]0.154321[/C][/ROW]
[ROW][C][15,16[[/C][C]15.5[/C][C]35[/C][C]0.216049[/C][C]0.734568[/C][C]0.216049[/C][/ROW]
[ROW][C][16,17[[/C][C]16.5[/C][C]23[/C][C]0.141975[/C][C]0.876543[/C][C]0.141975[/C][/ROW]
[ROW][C][17,18[[/C][C]17.5[/C][C]12[/C][C]0.074074[/C][C]0.950617[/C][C]0.074074[/C][/ROW]
[ROW][C][18,19][/C][C]18.5[/C][C]8[/C][C]0.049383[/C][C]1[/C][C]0.049383[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194132&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194132&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
[7,8[7.510.0061730.0061730.006173
[8,9[8.510.0061730.0123460.006173
[9,10[9.560.0370370.0493830.037037
[10,11[10.540.0246910.0740740.024691
[11,12[11.5120.0740740.1481480.074074
[12,13[12.5160.0987650.2469140.098765
[13,14[13.5190.1172840.3641980.117284
[14,15[14.5250.1543210.5185190.154321
[15,16[15.5350.2160490.7345680.216049
[16,17[16.5230.1419750.8765430.141975
[17,18[17.5120.0740740.9506170.074074
[18,19]18.580.04938310.049383



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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- ''
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')
}