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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 15 Dec 2012 08:47:52 -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/Dec/15/t1355579657y14pe8jk3cp5ezu.htm/, Retrieved Tue, 30 Apr 2024 11:39:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199929, Retrieved Tue, 30 Apr 2024 11:39:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Frequency Plot - ...] [2012-12-15 13:47:52] [09cdab5d933081235930b6410ef38881] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'1280x1024'
'1024x768'
'1120x700'
'1024x768'
'1280x800'
'1280x1024'
'1280x800'
'1024x768'
'1280x800'
'1280x1024'
'1280x800'
'1280x800'
'1280x1024'
'1688x949'
'1440x900'
'1600x1200'
'1280x800'
'1280x800'
'1280x768'
'1176x735'
'1280x800'
'1503x845'
'1440x900'
'1366x768'
'1280x768'
'1024x768'
'1280x800'
'2560x1440'
'1280x768'
'1024x768'
'1280x1024'
'1280x800'
'1440x900'
'1280x800'
'1440x900'
'1024x768'
'1440x900'
'1143x857'
'1280x800'
'1440x900'
'1280x800'
'1366x768'
'1024x768'
'1408x880'
'1366x768'
'1176x735'
'1920x1200'
'1257x785'
'1280x800'
'1280x800'
'1440x900'
'1680x1050'
'1440x900'
'1024x768'
'1140x641'
'1280x1024'
'1280x800'
'1280x800'
'1280x800'
'1280x800'
'1440x900'
'1280x800'
'1152x864'
'1280x1024'
'1280x800'
'1440x900'
'1280x800'
'1280x1024'
'1440x900'
'1280x800'
'1280x800'
'1440x900'
'1280x800'
'1280x1024'
'1600x900'
'1024x768'
'1366x768'
'1280x800'
'1280x800'
'1440x900'
'1366x768'
'1280x800'
'1024x768'
'1280x800'
'1440x900'
'1280x800'
'1280x800'
'1408x880'
'1280x800'
'1600x900'
'1600x900'
'1680x1050'
'1440x900'
'1440x900'
'917x550'
'1280x800'
'1760x990'
'1280x800'
'1280x800'
'1280x800'
'1024x768'
'1366x768'
'1440x900'
'1280x800'
'1280x1024'
'1920x1080'
'1024x768'
'1024x768'
'1600x900'
'1117x698'
'1440x900'
'983x737'
'1024x768'
'1024x640'
'1280x800'
'1440x900'
'1280x800'
'1280x800'
'1280x800'
'1440x900'
'1280x800'
'1024x768'
'1024x768'
'1152x864'
'1280x768'
'1024x768'
'1366x768'
'1680x1050'
'1680x1050'
'1280x800'
'1366x768'
'1024x768'
'1440x900'
'1024x768'
'1280x800'
'1280x800'
'1280x800'
'1024x768'
'1280x800'

Tables (Output of Computation)





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=199929&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=199929&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199929&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net






Frequency Table (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
1024x64010.0072
1024x768200.1439
1117x69810.0072
1120x70010.0072
1140x64110.0072
1143x85710.0072
1152x86420.0144
1176x73520.0144
1257x78510.0072
1280x1024100.0719
1280x76840.0288
1280x800470.3381
1366x76880.0576
1408x88020.0144
1440x900210.1511
1503x84510.0072
1600x120010.0072
1600x90040.0288
1680x105040.0288
1688x94910.0072
1760x99010.0072
1920x108010.0072
1920x120010.0072
2560x144010.0072
917x55010.0072
983x73710.0072

\begin{tabular}{lllllllll}
\hline
Frequency Table (Categorical Data) \tabularnewline
Category & Abs. Frequency & Rel. Frequency \tabularnewline
1024x640 & 1 & 0.0072 \tabularnewline
1024x768 & 20 & 0.1439 \tabularnewline
1117x698 & 1 & 0.0072 \tabularnewline
1120x700 & 1 & 0.0072 \tabularnewline
1140x641 & 1 & 0.0072 \tabularnewline
1143x857 & 1 & 0.0072 \tabularnewline
1152x864 & 2 & 0.0144 \tabularnewline
1176x735 & 2 & 0.0144 \tabularnewline
1257x785 & 1 & 0.0072 \tabularnewline
1280x1024 & 10 & 0.0719 \tabularnewline
1280x768 & 4 & 0.0288 \tabularnewline
1280x800 & 47 & 0.3381 \tabularnewline
1366x768 & 8 & 0.0576 \tabularnewline
1408x880 & 2 & 0.0144 \tabularnewline
1440x900 & 21 & 0.1511 \tabularnewline
1503x845 & 1 & 0.0072 \tabularnewline
1600x1200 & 1 & 0.0072 \tabularnewline
1600x900 & 4 & 0.0288 \tabularnewline
1680x1050 & 4 & 0.0288 \tabularnewline
1688x949 & 1 & 0.0072 \tabularnewline
1760x990 & 1 & 0.0072 \tabularnewline
1920x1080 & 1 & 0.0072 \tabularnewline
1920x1200 & 1 & 0.0072 \tabularnewline
2560x1440 & 1 & 0.0072 \tabularnewline
917x550 & 1 & 0.0072 \tabularnewline
983x737 & 1 & 0.0072 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199929&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]1024x640[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1024x768[/C][C]20[/C][C]0.1439[/C][/ROW]
[ROW][C]1117x698[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1120x700[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1140x641[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1143x857[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1152x864[/C][C]2[/C][C]0.0144[/C][/ROW]
[ROW][C]1176x735[/C][C]2[/C][C]0.0144[/C][/ROW]
[ROW][C]1257x785[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1280x1024[/C][C]10[/C][C]0.0719[/C][/ROW]
[ROW][C]1280x768[/C][C]4[/C][C]0.0288[/C][/ROW]
[ROW][C]1280x800[/C][C]47[/C][C]0.3381[/C][/ROW]
[ROW][C]1366x768[/C][C]8[/C][C]0.0576[/C][/ROW]
[ROW][C]1408x880[/C][C]2[/C][C]0.0144[/C][/ROW]
[ROW][C]1440x900[/C][C]21[/C][C]0.1511[/C][/ROW]
[ROW][C]1503x845[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1600x1200[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1600x900[/C][C]4[/C][C]0.0288[/C][/ROW]
[ROW][C]1680x1050[/C][C]4[/C][C]0.0288[/C][/ROW]
[ROW][C]1688x949[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1760x990[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1920x1080[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]1920x1200[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]2560x1440[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]917x550[/C][C]1[/C][C]0.0072[/C][/ROW]
[ROW][C]983x737[/C][C]1[/C][C]0.0072[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199929&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199929&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 (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
1024x64010.0072
1024x768200.1439
1117x69810.0072
1120x70010.0072
1140x64110.0072
1143x85710.0072
1152x86420.0144
1176x73520.0144
1257x78510.0072
1280x1024100.0719
1280x76840.0288
1280x800470.3381
1366x76880.0576
1408x88020.0144
1440x900210.1511
1503x84510.0072
1600x120010.0072
1600x90040.0288
1680x105040.0288
1688x94910.0072
1760x99010.0072
1920x108010.0072
1920x120010.0072
2560x144010.0072
917x55010.0072
983x73710.0072


Figures (Output of Computation)

Input Parameters & R Code

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):
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')
}