## 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 computationMon, 03 Oct 2011 12:11:34 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Oct/03/t1317658319hkw6hvi1e6kntb2.htm/, Retrieved Thu, 18 Jul 2024 03:04:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=125243, Retrieved Thu, 18 Jul 2024 03:04:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Workshop 1, task 1] [2011-10-03 16:11:34] [79818163420d1233b8d9d93d595e6c9e] [Current]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Taak 1 WS 6] [2011-11-11 16:49:06] [86f7284edee3dbb8ea5c7e2dec87d892]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Taak 1 WS 6] [2011-11-11 16:55:17] [86f7284edee3dbb8ea5c7e2dec87d892]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2011-11-11 17:11:18] [86f7284edee3dbb8ea5c7e2dec87d892]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2011-11-11 17:13:43] [86f7284edee3dbb8ea5c7e2dec87d892]
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Dataseries X:
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'Linuxi686'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'IntelMacOSX10_6_2'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.1'
'WindowsNT6.0'
'IntelMacOSX10_6_2'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'IntelMacOSX10_5_8'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'IntelMacOSX10_5_8'
'IntelMacOSX10_5_8'
'WindowsNT6.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.0'
'IntelMacOSX10_6_2'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'IntelMacOSX10_5_7'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT5.1'
'IntelMacOSX10_6_1'
'WindowsNT6.0'
'WindowsNT5.1'
'IntelMacOSX10.5'
'WindowsNT6.0'
'IntelMacOSX10_6'
'IntelMacOSX10_5_8'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.1'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT6.0'
'WindowsNT6.1'
'WindowsNT6.1'
'WindowsNT6.1'
'WindowsNT5.1'
'WindowsNT6.0'
'WindowsNT5.1'
'IntelMacOSX10_6_2'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT5.1'
'WindowsNT5.1'

 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 '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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=125243&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=125243&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=125243&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 'Gertrude Mary Cox' @ cox.wessa.net

 Frequency Table (Categorical Data) Category Abs. Frequency Rel. Frequency IntelMacOSX10.5 1 0.0072 IntelMacOSX10_5_7 1 0.0072 IntelMacOSX10_5_8 4 0.0288 IntelMacOSX10_6 1 0.0072 IntelMacOSX10_6_1 1 0.0072 IntelMacOSX10_6_2 4 0.0288 Linuxi686 1 0.0072 WindowsNT5.1 52 0.3741 WindowsNT6.0 65 0.4676 WindowsNT6.1 9 0.0647

\begin{tabular}{lllllllll}
\hline
Frequency Table (Categorical Data) \tabularnewline
Category & Abs. Frequency & Rel. Frequency \tabularnewline
IntelMacOSX10.5 & 1 & 0.0072 \tabularnewline
IntelMacOSX10_5_7 & 1 & 0.0072 \tabularnewline
IntelMacOSX10_5_8 & 4 & 0.0288 \tabularnewline
IntelMacOSX10_6 & 1 & 0.0072 \tabularnewline
IntelMacOSX10_6_1 & 1 & 0.0072 \tabularnewline
IntelMacOSX10_6_2 & 4 & 0.0288 \tabularnewline
Linuxi686 & 1 & 0.0072 \tabularnewline
WindowsNT5.1 & 52 & 0.3741 \tabularnewline
WindowsNT6.0 & 65 & 0.4676 \tabularnewline
WindowsNT6.1 & 9 & 0.0647 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=125243&T=1

[TABLE]
[ROW][C]Frequency Table (Categorical Data)[/C][/ROW]
[ROW][C]Category[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][/ROW]
[ROW][C]IntelMacOSX10.5[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]IntelMacOSX10_5_7[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]IntelMacOSX10_5_8[/C][C]4[/C][C]0.0288[/C][/ROW]
[ROW][C]IntelMacOSX10_6[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]IntelMacOSX10_6_1[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]IntelMacOSX10_6_2[/C][C]4[/C][C]0.0288[/C][/ROW]
[ROW][C]Linuxi686[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]WindowsNT5.1[/C][C]52[/C][C]0.3741[/C][/ROW]
[ROW][C]WindowsNT6.0[/C][C]65[/C][C]0.4676[/C][/ROW]
[ROW][C]WindowsNT6.1[/C][C]9[/C][C]0.0647[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=125243&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=125243&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 (Categorical Data) Category Abs. Frequency Rel. Frequency IntelMacOSX10.5 1 0.0072 IntelMacOSX10_5_7 1 0.0072 IntelMacOSX10_5_8 4 0.0288 IntelMacOSX10_6 1 0.0072 IntelMacOSX10_6_1 1 0.0072 IntelMacOSX10_6_2 4 0.0288 Linuxi686 1 0.0072 WindowsNT5.1 52 0.3741 WindowsNT6.0 65 0.4676 WindowsNT6.1 9 0.0647

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')}