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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 computationSun, 03 Oct 2010 20:06:48 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/03/t1286136449j4j1e9kj0eerafd.htm/, Retrieved Fri, 03 May 2024 10:03:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=80408, Retrieved Fri, 03 May 2024 10:03:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Histogram] [Frequency Plot (C...] [2010-09-25 09:09:15] [b98453cac15ba1066b407e146608df68]
F    D    [Histogram] [task1] [2010-10-03 20:06:48] [7a87ed98a7b21a29d6a45388a9b7b229] [Current]
Feedback Forum
2010-10-07 20:31:34 [411b43619fc9db329bbcdbf7261c55fb] [reply] 
Deze grafiek geeft de juiste informatie weer.

De auteur heeft reeds een poging ondernomen om de breedte van de X-as aan te passen. Dit met het doel om alle besturingssystemen (benaming) weer te geven.

Ik merk hierbij op dat de breedte nog te klein staat ingesteld om alle besturingssystemen te weergeven. Uit eigen ondervinding weet ik dat wanneer de breedte op 1200 staat, alle besturingssystemen verschijnen.

Een nadeel van het aanpassen van de breedte is wel dat het meer moeite kost om de verschillende frequenties op de grafiek af te lezen.

2010-10-08 16:00:09 [347d11d64cf4ded9ba0714e7297d928b] [reply] 
Correct (2/2).
De student heeft de juiste data gebruikt en een poging ondernomen om alle besturingssystemen op het scherm te krijgen.
2010-10-09 09:07:12 [] [reply] 
De juiste data werden gebruikt en er werd voor gezorgd dat de belangrijkste informatie afgelezen kan worden van de grafiek.
2010-10-09 13:19:42 [1047e32db976ffec0cf8e54ab6985f99] [reply] 
Goede blog, maar ik raad aan ook altijd een interpretatie van de gegevens te geven.
De frequency plot geeft weer hoe vaak een bepaald gegeven voorkomt. Je had dus kunnen schrijven dat browser Windows de volledige top 3 in beslag neemt en dus het meest gebruikt wordt door studenten. Intel Mac wordt ook gebruikt door enkele studenten, maar is minder populair.
2010-10-10 12:55:04 [8a0bf75212d7db208bd70f6fc4a41d2e] [reply] 
Er werden de juiste gegevens gebruikt.
2010-10-10 15:00:07 [73b763ab03a59f488b4c9e04fda397bb] [reply] 
De student heeft de juiste gegevens (OS) gebruikt.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'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'

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80408&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80408&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80408&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Frequency Table (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
IntelMacOSX10.510.0072
IntelMacOSX10_5_710.0072
IntelMacOSX10_5_840.0288
IntelMacOSX10_610.0072
IntelMacOSX10_6_110.0072
IntelMacOSX10_6_240.0288
Linuxi68610.0072
WindowsNT5.1520.3741
WindowsNT6.0650.4676
WindowsNT6.190.0647

\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=80408&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=80408&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80408&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
IntelMacOSX10.510.0072
IntelMacOSX10_5_710.0072
IntelMacOSX10_5_840.0288
IntelMacOSX10_610.0072
IntelMacOSX10_6_110.0072
IntelMacOSX10_6_240.0288
Linuxi68610.0072
WindowsNT5.1520.3741
WindowsNT6.0650.4676
WindowsNT6.190.0647


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 {
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')
}