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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 28 Dec 2012 18:00:13 -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/28/t1356735663r21rprcsvndw89w.htm/, Retrieved Mon, 29 Apr 2024 08:50:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204850, Retrieved Mon, 29 Apr 2024 08:50:53 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Prijsindexcijfers...] [2012-10-08 11:52:14] [873b10c79bed0b14ae85834791a7b7d7]
- R PD  [Univariate Data Series] [De maximumprijs o...] [2012-10-08 12:15:53] [873b10c79bed0b14ae85834791a7b7d7]
- RMPD    [Histogram] [] [2012-10-08 12:33:30] [873b10c79bed0b14ae85834791a7b7d7]
-   P         [Histogram] [] [2012-12-28 23:00:13] [12a829110dd20fa9d6217123dd6d88b6] [Current]
-   PD          [Histogram] [] [2012-12-28 23:01:50] [54245c9fde9e3f0baa063b8b8eee5d9b]
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Dataseries X:
65
65,3
62,9
63,5
62,1
59,3
61,6
61,5
60,1
59,5
62,7
65,5
63,8
63,8
62,7
62,3
62,4
64,8
66,4
65,1
67,4
68,8
68,6
71,5
75
84,3
84
79,1
78,8
82,7
85,3
84,5
80,8
70,1
68,2
68,1
72,3
73,1
71,5
74,1
80,3
80,6
81,4
87,4
89,3
93,2
92,8
96,8
100,3
95,6
89
87,4
86,7
92,8
98,6
100,8
105,5
107,8
113,7
120,3
126,5
134,8
134,5
133,1
128,8
127,1
129,1
128,4
126,5
117,1
114,2
109,1




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=204850&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=204850&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204850&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'George Udny Yule' @ yule.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[55,60[57.520.0277780.0277780.005556
[60,65[62.5130.1805560.2083330.036111
[65,70[67.5100.1388890.3472220.027778
[70,75[72.560.0833330.4305560.016667
[75,80[77.530.0416670.4722220.008333
[80,85[82.580.1111110.5833330.022222
[85,90[87.560.0833330.6666670.016667
[90,95[92.530.0416670.7083330.008333
[95,100[97.530.0416670.750.008333
[100,105[102.520.0277780.7777780.005556
[105,110[107.530.0416670.8194440.008333
[110,115[112.520.0277780.8472220.005556
[115,120[117.510.0138890.8611110.002778
[120,125[122.510.0138890.8750.002778
[125,130[127.560.0833330.9583330.016667
[130,135]132.530.04166710.008333

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[55,60[ & 57.5 & 2 & 0.027778 & 0.027778 & 0.005556 \tabularnewline
[60,65[ & 62.5 & 13 & 0.180556 & 0.208333 & 0.036111 \tabularnewline
[65,70[ & 67.5 & 10 & 0.138889 & 0.347222 & 0.027778 \tabularnewline
[70,75[ & 72.5 & 6 & 0.083333 & 0.430556 & 0.016667 \tabularnewline
[75,80[ & 77.5 & 3 & 0.041667 & 0.472222 & 0.008333 \tabularnewline
[80,85[ & 82.5 & 8 & 0.111111 & 0.583333 & 0.022222 \tabularnewline
[85,90[ & 87.5 & 6 & 0.083333 & 0.666667 & 0.016667 \tabularnewline
[90,95[ & 92.5 & 3 & 0.041667 & 0.708333 & 0.008333 \tabularnewline
[95,100[ & 97.5 & 3 & 0.041667 & 0.75 & 0.008333 \tabularnewline
[100,105[ & 102.5 & 2 & 0.027778 & 0.777778 & 0.005556 \tabularnewline
[105,110[ & 107.5 & 3 & 0.041667 & 0.819444 & 0.008333 \tabularnewline
[110,115[ & 112.5 & 2 & 0.027778 & 0.847222 & 0.005556 \tabularnewline
[115,120[ & 117.5 & 1 & 0.013889 & 0.861111 & 0.002778 \tabularnewline
[120,125[ & 122.5 & 1 & 0.013889 & 0.875 & 0.002778 \tabularnewline
[125,130[ & 127.5 & 6 & 0.083333 & 0.958333 & 0.016667 \tabularnewline
[130,135] & 132.5 & 3 & 0.041667 & 1 & 0.008333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204850&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][55,60[[/C][C]57.5[/C][C]2[/C][C]0.027778[/C][C]0.027778[/C][C]0.005556[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]13[/C][C]0.180556[/C][C]0.208333[/C][C]0.036111[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]10[/C][C]0.138889[/C][C]0.347222[/C][C]0.027778[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]6[/C][C]0.083333[/C][C]0.430556[/C][C]0.016667[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]3[/C][C]0.041667[/C][C]0.472222[/C][C]0.008333[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]8[/C][C]0.111111[/C][C]0.583333[/C][C]0.022222[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]6[/C][C]0.083333[/C][C]0.666667[/C][C]0.016667[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]3[/C][C]0.041667[/C][C]0.708333[/C][C]0.008333[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]3[/C][C]0.041667[/C][C]0.75[/C][C]0.008333[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]2[/C][C]0.027778[/C][C]0.777778[/C][C]0.005556[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]3[/C][C]0.041667[/C][C]0.819444[/C][C]0.008333[/C][/ROW]
[ROW][C][110,115[[/C][C]112.5[/C][C]2[/C][C]0.027778[/C][C]0.847222[/C][C]0.005556[/C][/ROW]
[ROW][C][115,120[[/C][C]117.5[/C][C]1[/C][C]0.013889[/C][C]0.861111[/C][C]0.002778[/C][/ROW]
[ROW][C][120,125[[/C][C]122.5[/C][C]1[/C][C]0.013889[/C][C]0.875[/C][C]0.002778[/C][/ROW]
[ROW][C][125,130[[/C][C]127.5[/C][C]6[/C][C]0.083333[/C][C]0.958333[/C][C]0.016667[/C][/ROW]
[ROW][C][130,135][/C][C]132.5[/C][C]3[/C][C]0.041667[/C][C]1[/C][C]0.008333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204850&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204850&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
[55,60[57.520.0277780.0277780.005556
[60,65[62.5130.1805560.2083330.036111
[65,70[67.5100.1388890.3472220.027778
[70,75[72.560.0833330.4305560.016667
[75,80[77.530.0416670.4722220.008333
[80,85[82.580.1111110.5833330.022222
[85,90[87.560.0833330.6666670.016667
[90,95[92.530.0416670.7083330.008333
[95,100[97.530.0416670.750.008333
[100,105[102.520.0277780.7777780.005556
[105,110[107.530.0416670.8194440.008333
[110,115[112.520.0277780.8472220.005556
[115,120[117.510.0138890.8611110.002778
[120,125[122.510.0138890.8750.002778
[125,130[127.560.0833330.9583330.016667
[130,135]132.530.04166710.008333



Parameters (Session):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 20 ; 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')
}