Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 05 Oct 2010 13:39:16 +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/05/t12862859156x3ishxzk5rol4g.htm/, Retrieved Sat, 27 Apr 2024 23:24:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=81438, Retrieved Sat, 27 Apr 2024 23:24:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords KDGP1W22
Estimated Impact150
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Consumptieprijs i...] [2010-09-28 13:06:31] [04d4ebd708b081bb203cd3af96bd9a4a]
- RMP     [Histogram] [Consumptieprijs i...] [2010-10-05 13:39:16] [c4eb40020db64a143131e9d41e371811] [Current]
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Dataseries X:
101.02
101.15
101.51
101.75
101.8
101.8
101.8
101.82
101.99
102.25
102.34
102.35
102.35
102.39
102.49
102.67
102.68
102.7
102.71
102.72
102.83
102.92
103.04
103.08
103.09
103.11
103.18
103.18
103.22
103.25
103.25
103.25
103.47
103.57
103.66
103.7
103.7
103.75
103.85
104.02
104.13
104.17
104.18
104.2
104.5
104.78
104.88
104.89
104.9
104.95
105.24
105.35
105.44
105.46
105.47
105.48
105.75
106.1
106.19
106.23
106.24
106.25
106.35
106.48
106.52
106.55
106.55
106.56
106.89
107.09
107.24
107.28
107.3
107.31
107.47
107.35
107.31
107.32
107.32
107.34
107.53
107.72
107.75
107.79
107.81
107.9
107.8
107.86
107.8
107.74
107.75
107.83
107.8
107.81
107.86
107.83





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=81438&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=81438&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=81438&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[101,102[101.590.093750.093750.09375
[102,103[102.5130.1354170.2291670.135417
[103,104[103.5170.1770830.406250.177083
[104,105[104.5110.1145830.5208330.114583
[105,106[105.570.0729170.593750.072917
[106,107[106.5120.1250.718750.125
[107,108]107.5270.2812510.28125

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[101,102[ & 101.5 & 9 & 0.09375 & 0.09375 & 0.09375 \tabularnewline
[102,103[ & 102.5 & 13 & 0.135417 & 0.229167 & 0.135417 \tabularnewline
[103,104[ & 103.5 & 17 & 0.177083 & 0.40625 & 0.177083 \tabularnewline
[104,105[ & 104.5 & 11 & 0.114583 & 0.520833 & 0.114583 \tabularnewline
[105,106[ & 105.5 & 7 & 0.072917 & 0.59375 & 0.072917 \tabularnewline
[106,107[ & 106.5 & 12 & 0.125 & 0.71875 & 0.125 \tabularnewline
[107,108] & 107.5 & 27 & 0.28125 & 1 & 0.28125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=81438&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][101,102[[/C][C]101.5[/C][C]9[/C][C]0.09375[/C][C]0.09375[/C][C]0.09375[/C][/ROW]
[ROW][C][102,103[[/C][C]102.5[/C][C]13[/C][C]0.135417[/C][C]0.229167[/C][C]0.135417[/C][/ROW]
[ROW][C][103,104[[/C][C]103.5[/C][C]17[/C][C]0.177083[/C][C]0.40625[/C][C]0.177083[/C][/ROW]
[ROW][C][104,105[[/C][C]104.5[/C][C]11[/C][C]0.114583[/C][C]0.520833[/C][C]0.114583[/C][/ROW]
[ROW][C][105,106[[/C][C]105.5[/C][C]7[/C][C]0.072917[/C][C]0.59375[/C][C]0.072917[/C][/ROW]
[ROW][C][106,107[[/C][C]106.5[/C][C]12[/C][C]0.125[/C][C]0.71875[/C][C]0.125[/C][/ROW]
[ROW][C][107,108][/C][C]107.5[/C][C]27[/C][C]0.28125[/C][C]1[/C][C]0.28125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=81438&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=81438&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
[101,102[101.590.093750.093750.09375
[102,103[102.5130.1354170.2291670.135417
[103,104[103.5170.1770830.406250.177083
[104,105[104.5110.1145830.5208330.114583
[105,106[105.570.0729170.593750.072917
[106,107[106.5120.1250.718750.125
[107,108]107.5270.2812510.28125



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')
}