Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 07 Jan 2013 19:23:18 -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/2013/Jan/07/t135760463275t76ebtxp8xl7t.htm/, Retrieved Wed, 01 May 2024 11:34:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205048, Retrieved Wed, 01 May 2024 11:34:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords6 klassen
Estimated Impact180
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Gemiddelde consum...] [2013-01-07 15:57:01] [1d73611e45a05aa2060be114fa39c596]
- RMP     [Histogram] [Opgave 2 opdracht...] [2013-01-08 00:23:18] [40325e7317026cf0d36242170f65df44] [Current]
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Dataseries X:
101.81
101.72
101.78
102.04
102.36
102.56
102.69
102.77
102.85
102.9
102.72
102.79
102.9
102.91
103.29
103.35
102.97
103.05
103.18
103.21
103.32
103.31
103.6
103.68
103.77
103.82
103.86
103.9
103.63
103.65
103.7
103.77
103.94
104.03
104.03
104.29
104.35
104.67
104.73
104.86
104.05
104.15
104.27
104.33
104.41
104.4
104.41
104.6
104.61
104.65
104.55
104.51
104.74
104.89
104.91
104.93
104.95
104.97
105.16
105.29
105.35
105.36
105.45
105.3
105.73
105.86
105.85
105.95
105.97
106.15
105.37
105.39




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205048&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205048&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205048&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[101,102[101.530.0416670.0416670.041667
[102,103[102.5120.1666670.2083330.166667
[103,104[103.5180.250.4583330.25
[104,105[104.5250.3472220.8055560.347222
[105,106[105.5130.1805560.9861110.180556
[106,107]106.510.01388910.013889

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[101,102[ & 101.5 & 3 & 0.041667 & 0.041667 & 0.041667 \tabularnewline
[102,103[ & 102.5 & 12 & 0.166667 & 0.208333 & 0.166667 \tabularnewline
[103,104[ & 103.5 & 18 & 0.25 & 0.458333 & 0.25 \tabularnewline
[104,105[ & 104.5 & 25 & 0.347222 & 0.805556 & 0.347222 \tabularnewline
[105,106[ & 105.5 & 13 & 0.180556 & 0.986111 & 0.180556 \tabularnewline
[106,107] & 106.5 & 1 & 0.013889 & 1 & 0.013889 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205048&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]3[/C][C]0.041667[/C][C]0.041667[/C][C]0.041667[/C][/ROW]
[ROW][C][102,103[[/C][C]102.5[/C][C]12[/C][C]0.166667[/C][C]0.208333[/C][C]0.166667[/C][/ROW]
[ROW][C][103,104[[/C][C]103.5[/C][C]18[/C][C]0.25[/C][C]0.458333[/C][C]0.25[/C][/ROW]
[ROW][C][104,105[[/C][C]104.5[/C][C]25[/C][C]0.347222[/C][C]0.805556[/C][C]0.347222[/C][/ROW]
[ROW][C][105,106[[/C][C]105.5[/C][C]13[/C][C]0.180556[/C][C]0.986111[/C][C]0.180556[/C][/ROW]
[ROW][C][106,107][/C][C]106.5[/C][C]1[/C][C]0.013889[/C][C]1[/C][C]0.013889[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205048&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205048&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[101.530.0416670.0416670.041667
[102,103[102.5120.1666670.2083330.166667
[103,104[103.5180.250.4583330.25
[104,105[104.5250.3472220.8055560.347222
[105,106[105.5130.1805560.9861110.180556
[106,107]106.510.01388910.013889



Parameters (Session):
par1 = 6 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 6 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '6'
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')
}