## Free Statistics

of Irreproducible Research!

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 Wed, 29 Mar 2023 20:04:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194132, Retrieved Wed, 29 Mar 2023 20:04:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'George Udny Yule' @ yule.wessa.net

 Frequency Table (Histogram) Bins Midpoint Abs. Frequency Rel. Frequency Cumul. Rel. Freq. Density [7,8[ 7.5 1 0.006173 0.006173 0.006173 [8,9[ 8.5 1 0.006173 0.012346 0.006173 [9,10[ 9.5 6 0.037037 0.049383 0.037037 [10,11[ 10.5 4 0.024691 0.074074 0.024691 [11,12[ 11.5 12 0.074074 0.148148 0.074074 [12,13[ 12.5 16 0.098765 0.246914 0.098765 [13,14[ 13.5 19 0.117284 0.364198 0.117284 [14,15[ 14.5 25 0.154321 0.518519 0.154321 [15,16[ 15.5 35 0.216049 0.734568 0.216049 [16,17[ 16.5 23 0.141975 0.876543 0.141975 [17,18[ 17.5 12 0.074074 0.950617 0.074074 [18,19] 18.5 8 0.049383 1 0.049383

\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) Bins Midpoint Abs. Frequency Rel. Frequency Cumul. Rel. Freq. Density [7,8[ 7.5 1 0.006173 0.006173 0.006173 [8,9[ 8.5 1 0.006173 0.012346 0.006173 [9,10[ 9.5 6 0.037037 0.049383 0.037037 [10,11[ 10.5 4 0.024691 0.074074 0.024691 [11,12[ 11.5 12 0.074074 0.148148 0.074074 [12,13[ 12.5 16 0.098765 0.246914 0.098765 [13,14[ 13.5 19 0.117284 0.364198 0.117284 [14,15[ 14.5 25 0.154321 0.518519 0.154321 [15,16[ 15.5 35 0.216049 0.734568 0.216049 [16,17[ 16.5 23 0.141975 0.876543 0.141975 [17,18[ 17.5 12 0.074074 0.950617 0.074074 [18,19] 18.5 8 0.049383 1 0.049383

par4 <- 'Unknown'par3 <- 'FALSE'par2 <- 'grey'par1 <- ''par1 <- as.numeric(par1)if (par3 == 'TRUE') par3 <- TRUEif (par3 == 'FALSE') par3 <- FALSEif (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 <- 3if (par1 > 50) par1 <- 50myhist<-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])) {myhistn <- 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 <- 0if (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='')elsedum <- paste(mybracket,myhist$breaks[i],sep='')dum <- paste(dum,myhist$breaks[i+1],sep=',')if (i==mynumrows)dum <- paste(dum,']',sep='')elsedum <- 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$counts[i]/ncrf <- crf + rfa<-table.element(a,round(rf,6))a<-table.element(a,round(crf,6))a<-table.element(a,round(myhist$density[i],6))a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable.tab')} else {mytabreltab <- 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')}