Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 28 Sep 2016 14:09:19 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Sep/28/t1475068360lqk2yp0ss782anj.htm/, Retrieved Sun, 05 May 2024 22:31:04 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 05 May 2024 22:31:04 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
662
670
659
663
673
699
712
700
692
699
700
702
693
696
696
694
695
715
731
715
707
712
699
703
695
694
691
694
699
720
732
712
705
707
700
687
674
676
666
669
669
688
705
684
679
689
691
685
690
685
688
696
693
721
726
704
700
707
696
687




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[650,660[65510.0166670.0166670.001667
[660,670[66550.0833330.10.008333
[670,680[67550.0833330.1833330.008333
[680,690[68580.1333330.3166670.013333
[690,700[695190.3166670.6333330.031667
[700,710[705120.20.8333330.02
[710,720[71550.0833330.9166670.008333
[720,730[72530.050.9666670.005
[730,740]73520.03333310.003333

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[650,660[ & 655 & 1 & 0.016667 & 0.016667 & 0.001667 \tabularnewline
[660,670[ & 665 & 5 & 0.083333 & 0.1 & 0.008333 \tabularnewline
[670,680[ & 675 & 5 & 0.083333 & 0.183333 & 0.008333 \tabularnewline
[680,690[ & 685 & 8 & 0.133333 & 0.316667 & 0.013333 \tabularnewline
[690,700[ & 695 & 19 & 0.316667 & 0.633333 & 0.031667 \tabularnewline
[700,710[ & 705 & 12 & 0.2 & 0.833333 & 0.02 \tabularnewline
[710,720[ & 715 & 5 & 0.083333 & 0.916667 & 0.008333 \tabularnewline
[720,730[ & 725 & 3 & 0.05 & 0.966667 & 0.005 \tabularnewline
[730,740] & 735 & 2 & 0.033333 & 1 & 0.003333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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][650,660[[/C][C]655[/C][C]1[/C][C]0.016667[/C][C]0.016667[/C][C]0.001667[/C][/ROW]
[ROW][C][660,670[[/C][C]665[/C][C]5[/C][C]0.083333[/C][C]0.1[/C][C]0.008333[/C][/ROW]
[ROW][C][670,680[[/C][C]675[/C][C]5[/C][C]0.083333[/C][C]0.183333[/C][C]0.008333[/C][/ROW]
[ROW][C][680,690[[/C][C]685[/C][C]8[/C][C]0.133333[/C][C]0.316667[/C][C]0.013333[/C][/ROW]
[ROW][C][690,700[[/C][C]695[/C][C]19[/C][C]0.316667[/C][C]0.633333[/C][C]0.031667[/C][/ROW]
[ROW][C][700,710[[/C][C]705[/C][C]12[/C][C]0.2[/C][C]0.833333[/C][C]0.02[/C][/ROW]
[ROW][C][710,720[[/C][C]715[/C][C]5[/C][C]0.083333[/C][C]0.916667[/C][C]0.008333[/C][/ROW]
[ROW][C][720,730[[/C][C]725[/C][C]3[/C][C]0.05[/C][C]0.966667[/C][C]0.005[/C][/ROW]
[ROW][C][730,740][/C][C]735[/C][C]2[/C][C]0.033333[/C][C]1[/C][C]0.003333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
[650,660[65510.0166670.0166670.001667
[660,670[66550.0833330.10.008333
[670,680[67550.0833330.1833330.008333
[680,690[68580.1333330.3166670.013333
[690,700[695190.3166670.6333330.031667
[700,710[705120.20.8333330.02
[710,720[71550.0833330.9166670.008333
[720,730[72530.050.9666670.005
[730,740]73520.03333310.003333



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 {
barplot(mytab <- sort(table(x),T),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')
}