Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 02 Oct 2015 16:38:25 +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/2015/Oct/02/t14438003954iw7s7pwanfssfw.htm/, Retrieved Mon, 13 May 2024 22:32:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281146, Retrieved Mon, 13 May 2024 22:32:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2015-09-30 07:28:46] [29a2eb7f0693cbc9420fc4e9708ffcae]
- RMPD    [Histogram] [] [2015-10-02 15:38:25] [ba98afd91fb48c18835dffdfcacd1aba] [Current]
- R P       [Histogram] [] [2015-10-02 15:40:53] [29a2eb7f0693cbc9420fc4e9708ffcae]
- RMP       [Kernel Density Estimation] [] [2015-10-02 16:00:24] [29a2eb7f0693cbc9420fc4e9708ffcae]
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Dataseries X:
104.37
104.66
104.88
105.08
104.53
104.97
105.73
106.11
106.16
106.53
107.23
107.56
106.46
107.42
107.84
108.65
107.58
107.67
107.09
106.96
107.63
108.03
107.33
107.16
106.28
107.26
106.48
106.82
106.9
106.6
106.79
107.19
106.34
106.91
106.55
106.73
106.36
107.07
106.96
107.82
108.07
108.11
108.16
108.29
108.5
108.69
109.12
108.82
108.07
109.92
109.24
109.9
109.7
110.15
109.73
109.62
110.42
110.69
110.75
111.41
110.56
110.88
111.35
110.31
111.63
111.24
111.66
111.44
110.72
111.19
110.07
110.86
110.46
111
111.11
111.9
111.38
111.69
111.65
111.98
111.63
112.57
112.38
111.73




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281146&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]1 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=281146&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281146&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[104,105[104.550.0595240.0595240.059524
[105,106[105.520.023810.0833330.02381
[106,107[106.5170.2023810.2857140.202381
[107,108[107.5140.1666670.4523810.166667
[108,109[108.5100.1190480.5714290.119048
[109,110[109.570.0833330.6547620.083333
[110,111[110.5110.1309520.7857140.130952
[111,112[111.5160.1904760.976190.190476
[112,113]112.520.0238110.02381

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[104,105[ & 104.5 & 5 & 0.059524 & 0.059524 & 0.059524 \tabularnewline
[105,106[ & 105.5 & 2 & 0.02381 & 0.083333 & 0.02381 \tabularnewline
[106,107[ & 106.5 & 17 & 0.202381 & 0.285714 & 0.202381 \tabularnewline
[107,108[ & 107.5 & 14 & 0.166667 & 0.452381 & 0.166667 \tabularnewline
[108,109[ & 108.5 & 10 & 0.119048 & 0.571429 & 0.119048 \tabularnewline
[109,110[ & 109.5 & 7 & 0.083333 & 0.654762 & 0.083333 \tabularnewline
[110,111[ & 110.5 & 11 & 0.130952 & 0.785714 & 0.130952 \tabularnewline
[111,112[ & 111.5 & 16 & 0.190476 & 0.97619 & 0.190476 \tabularnewline
[112,113] & 112.5 & 2 & 0.02381 & 1 & 0.02381 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281146&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][104,105[[/C][C]104.5[/C][C]5[/C][C]0.059524[/C][C]0.059524[/C][C]0.059524[/C][/ROW]
[ROW][C][105,106[[/C][C]105.5[/C][C]2[/C][C]0.02381[/C][C]0.083333[/C][C]0.02381[/C][/ROW]
[ROW][C][106,107[[/C][C]106.5[/C][C]17[/C][C]0.202381[/C][C]0.285714[/C][C]0.202381[/C][/ROW]
[ROW][C][107,108[[/C][C]107.5[/C][C]14[/C][C]0.166667[/C][C]0.452381[/C][C]0.166667[/C][/ROW]
[ROW][C][108,109[[/C][C]108.5[/C][C]10[/C][C]0.119048[/C][C]0.571429[/C][C]0.119048[/C][/ROW]
[ROW][C][109,110[[/C][C]109.5[/C][C]7[/C][C]0.083333[/C][C]0.654762[/C][C]0.083333[/C][/ROW]
[ROW][C][110,111[[/C][C]110.5[/C][C]11[/C][C]0.130952[/C][C]0.785714[/C][C]0.130952[/C][/ROW]
[ROW][C][111,112[[/C][C]111.5[/C][C]16[/C][C]0.190476[/C][C]0.97619[/C][C]0.190476[/C][/ROW]
[ROW][C][112,113][/C][C]112.5[/C][C]2[/C][C]0.02381[/C][C]1[/C][C]0.02381[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281146&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281146&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
[104,105[104.550.0595240.0595240.059524
[105,106[105.520.023810.0833330.02381
[106,107[106.5170.2023810.2857140.202381
[107,108[107.5140.1666670.4523810.166667
[108,109[108.5100.1190480.5714290.119048
[109,110[109.570.0833330.6547620.083333
[110,111[110.5110.1309520.7857140.130952
[111,112[111.5160.1904760.976190.190476
[112,113]112.520.0238110.02381



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 {
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')
}