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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 26 Sep 2016 22:39:13 +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/26/t1474926110bt58wew0786ya04.htm/, Retrieved Thu, 09 May 2024 03:39:42 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Thu, 09 May 2024 03:39:42 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
789
811
996
778
603
990
735
800
706
766
870
647
726
784
884
696
893
674
703
799
793
799
1 022
758
1 021
944
915
864
1 022
891
1 087
822
890
1 092
967
833
1 104
1 063
1 103
1 039
1 185
1 047
1 155
878
879
1 133
920
943
938
900
781
1 040
792
653
866
679
799
760
699
762
671
679
862
624
516
650
583
444
562
540
524
683

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.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]'Gwilym Jenkins' @ jenkins.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:  
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'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[400,500[45010.0138890.0138890.000139
[500,600[55050.0694440.0833330.000694
[600,700[650120.1666670.250.001667
[700,800[750170.2361110.4861110.002361
[800,900[850140.1944440.6805560.001944
[900,1000[95090.1250.8055560.00125
[1000,1100[105090.1250.9305560.00125
[1100,1200]115050.06944410.000694

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[400,500[ & 450 & 1 & 0.013889 & 0.013889 & 0.000139 \tabularnewline
[500,600[ & 550 & 5 & 0.069444 & 0.083333 & 0.000694 \tabularnewline
[600,700[ & 650 & 12 & 0.166667 & 0.25 & 0.001667 \tabularnewline
[700,800[ & 750 & 17 & 0.236111 & 0.486111 & 0.002361 \tabularnewline
[800,900[ & 850 & 14 & 0.194444 & 0.680556 & 0.001944 \tabularnewline
[900,1000[ & 950 & 9 & 0.125 & 0.805556 & 0.00125 \tabularnewline
[1000,1100[ & 1050 & 9 & 0.125 & 0.930556 & 0.00125 \tabularnewline
[1100,1200] & 1150 & 5 & 0.069444 & 1 & 0.000694 \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][400,500[[/C][C]450[/C][C]1[/C][C]0.013889[/C][C]0.013889[/C][C]0.000139[/C][/ROW]
[ROW][C][500,600[[/C][C]550[/C][C]5[/C][C]0.069444[/C][C]0.083333[/C][C]0.000694[/C][/ROW]
[ROW][C][600,700[[/C][C]650[/C][C]12[/C][C]0.166667[/C][C]0.25[/C][C]0.001667[/C][/ROW]
[ROW][C][700,800[[/C][C]750[/C][C]17[/C][C]0.236111[/C][C]0.486111[/C][C]0.002361[/C][/ROW]
[ROW][C][800,900[[/C][C]850[/C][C]14[/C][C]0.194444[/C][C]0.680556[/C][C]0.001944[/C][/ROW]
[ROW][C][900,1000[[/C][C]950[/C][C]9[/C][C]0.125[/C][C]0.805556[/C][C]0.00125[/C][/ROW]
[ROW][C][1000,1100[[/C][C]1050[/C][C]9[/C][C]0.125[/C][C]0.930556[/C][C]0.00125[/C][/ROW]
[ROW][C][1100,1200][/C][C]1150[/C][C]5[/C][C]0.069444[/C][C]1[/C][C]0.000694[/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:  
QR Code


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

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[400,500[45010.0138890.0138890.000139
[500,600[55050.0694440.0833330.000694
[600,700[650120.1666670.250.001667
[700,800[750170.2361110.4861110.002361
[800,900[850140.1944440.6805560.001944
[900,1000[95090.1250.8055560.00125
[1000,1100[105090.1250.9305560.00125
[1100,1200]115050.06944410.000694


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par2 = blue ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = ; par2 = blue ; 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 {
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')
}