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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 02 Oct 2015 12:27:47 +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/t14437854418e37mjr59iujwt7.htm/, Retrieved Tue, 14 May 2024 07:32:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281058, Retrieved Tue, 14 May 2024 07:32:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2015-10-02 11:27:47] [237b8e3b7b7bc12136ba0893525d9132] [Current]
- RM      [Histogram] [] [2015-10-03 08:56:28] [3d706eb9e86fdfd3fd9fb35c51d0be98]
- R PD    [Histogram] [] [2015-10-03 09:00:10] [3d706eb9e86fdfd3fd9fb35c51d0be98]
- RMPD    [Kernel Density Estimation] [] [2015-10-03 09:18:28] [3d706eb9e86fdfd3fd9fb35c51d0be98]
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Dataseries X:
71,83
71,39
73,71
74,13
74,45
74,95
75,09
75,23
76,11
76,64
76,97
78,23
77,15
76,33
70,19
68,42
66,49
63,41
62,92
65,53
65,26
68,25
74,39
78,71
82,15
86,05
89,46
89,32
88,94
93,35
94,72
96,11
104,06
104,11
103,9
110,75
110,82
107,59
96,03
95,69
90,63
75,87
75,57
78,78
74,93
75,85
75,49
76,87
78,18
79,37
80,59
81,18
81,02
82,75
83,63
85,35
90,52
90,66
90,69
92,56
92,87
93,82
96,32
96,03
96,53
102,96
102,38
102,66
106,83
106,5
106,78
108,49
108,77
110,43
110,84
110,52
110,11
109,42
109,06
108,98
108,36
108,11
108,44
107,76
106,27
101,07
100,79
100,97
99,33
99,35
99,23
98,14
98,17
98,48
99
99,19
99,1
100,13
100,07
95,26
94,72
94,25
89,46
88,38
88,57
93,82
93,94
93,92




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=281058&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=281058&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281058&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
[60,65[62.520.0185190.0185190.003704
[65,70[67.550.0462960.0648150.009259
[70,75[72.590.0833330.1481480.016667
[75,80[77.5170.1574070.3055560.031481
[80,85[82.560.0555560.3611110.011111
[85,90[87.580.0740740.4351850.014815
[90,95[92.5140.129630.5648150.025926
[95,100[97.5160.1481480.7129630.02963
[100,105[102.5110.1018520.8148150.02037
[105,110[107.5140.129630.9444440.025926
[110,115]112.560.05555610.011111

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[60,65[ & 62.5 & 2 & 0.018519 & 0.018519 & 0.003704 \tabularnewline
[65,70[ & 67.5 & 5 & 0.046296 & 0.064815 & 0.009259 \tabularnewline
[70,75[ & 72.5 & 9 & 0.083333 & 0.148148 & 0.016667 \tabularnewline
[75,80[ & 77.5 & 17 & 0.157407 & 0.305556 & 0.031481 \tabularnewline
[80,85[ & 82.5 & 6 & 0.055556 & 0.361111 & 0.011111 \tabularnewline
[85,90[ & 87.5 & 8 & 0.074074 & 0.435185 & 0.014815 \tabularnewline
[90,95[ & 92.5 & 14 & 0.12963 & 0.564815 & 0.025926 \tabularnewline
[95,100[ & 97.5 & 16 & 0.148148 & 0.712963 & 0.02963 \tabularnewline
[100,105[ & 102.5 & 11 & 0.101852 & 0.814815 & 0.02037 \tabularnewline
[105,110[ & 107.5 & 14 & 0.12963 & 0.944444 & 0.025926 \tabularnewline
[110,115] & 112.5 & 6 & 0.055556 & 1 & 0.011111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281058&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][60,65[[/C][C]62.5[/C][C]2[/C][C]0.018519[/C][C]0.018519[/C][C]0.003704[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]5[/C][C]0.046296[/C][C]0.064815[/C][C]0.009259[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]9[/C][C]0.083333[/C][C]0.148148[/C][C]0.016667[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]17[/C][C]0.157407[/C][C]0.305556[/C][C]0.031481[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]6[/C][C]0.055556[/C][C]0.361111[/C][C]0.011111[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]8[/C][C]0.074074[/C][C]0.435185[/C][C]0.014815[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]14[/C][C]0.12963[/C][C]0.564815[/C][C]0.025926[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]16[/C][C]0.148148[/C][C]0.712963[/C][C]0.02963[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]11[/C][C]0.101852[/C][C]0.814815[/C][C]0.02037[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]14[/C][C]0.12963[/C][C]0.944444[/C][C]0.025926[/C][/ROW]
[ROW][C][110,115][/C][C]112.5[/C][C]6[/C][C]0.055556[/C][C]1[/C][C]0.011111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281058&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281058&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
[60,65[62.520.0185190.0185190.003704
[65,70[67.550.0462960.0648150.009259
[70,75[72.590.0833330.1481480.016667
[75,80[77.5170.1574070.3055560.031481
[80,85[82.560.0555560.3611110.011111
[85,90[87.580.0740740.4351850.014815
[90,95[92.5140.129630.5648150.025926
[95,100[97.5160.1481480.7129630.02963
[100,105[102.5110.1018520.8148150.02037
[105,110[107.5140.129630.9444440.025926
[110,115]112.560.05555610.011111



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')
}