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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 14:00:33 +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/t1443790865oxrewiei5jjo69e.htm/, Retrieved Mon, 13 May 2024 23:56:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281093, Retrieved Mon, 13 May 2024 23:56:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [opgave 2 oefening...] [2015-10-02 13:00:33] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
85.13
85.54
85.47
85.78
86.07
86.05
86.32
86.43
86.41
86.38
86.59
86.68
86.87
87.32
87.13
87.42
87.22
87.17
87.52
87.49
87.53
87.93
88.54
88.96
89.3
90.01
90.52
90.64
91.25
91.59
92.09
91.81
92.03
92.15
91.98
92.11
92.28
92.53
91.97
92.05
91.87
91.49
91.48
91.63
91.46
91.61
91.7
91.87
92.21
92.65
92.83
93.02
93.33
93.35
93.45
93.51
93.8
93.94
94.02
94.26
94.71
95.26
95.54
95.69
96.03
96.4
96.55
96.45
96.65
96.84
97.21
97.31
97.91
98.51
98.54
98.52
98.66
98.53
98.71
98.92
98.96
99.25
99.32
99.41
99.36
99.58
99.77
99.77
100.03
100.2
100.24
100.1
100.03
100.18
100.29
100.41
100.6
100.75
100.79
100.44
100.29
100.34
100.46
100.12
100.06
100.28
100.28
100.4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281093&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281093&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281093&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'Herman Ole Andreas Wold' @ wold.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[85,86[85.540.0370370.0370370.037037
[86,87[86.590.0833330.120370.083333
[87,88[87.590.0833330.2037040.083333
[88,89[88.520.0185190.2222220.018519
[89,90[89.510.0092590.2314810.009259
[90,91[90.530.0277780.2592590.027778
[91,92[91.5130.120370.379630.12037
[92,93[92.5100.0925930.4722220.092593
[93,94[93.570.0648150.5370370.064815
[94,95[94.530.0277780.5648150.027778
[95,96[95.530.0277780.5925930.027778
[96,97[96.560.0555560.6481480.055556
[97,98[97.530.0277780.6759260.027778
[98,99[98.580.0740740.750.074074
[99,100[99.570.0648150.8148150.064815
[100,101]100.5200.18518510.185185

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[85,86[ & 85.5 & 4 & 0.037037 & 0.037037 & 0.037037 \tabularnewline
[86,87[ & 86.5 & 9 & 0.083333 & 0.12037 & 0.083333 \tabularnewline
[87,88[ & 87.5 & 9 & 0.083333 & 0.203704 & 0.083333 \tabularnewline
[88,89[ & 88.5 & 2 & 0.018519 & 0.222222 & 0.018519 \tabularnewline
[89,90[ & 89.5 & 1 & 0.009259 & 0.231481 & 0.009259 \tabularnewline
[90,91[ & 90.5 & 3 & 0.027778 & 0.259259 & 0.027778 \tabularnewline
[91,92[ & 91.5 & 13 & 0.12037 & 0.37963 & 0.12037 \tabularnewline
[92,93[ & 92.5 & 10 & 0.092593 & 0.472222 & 0.092593 \tabularnewline
[93,94[ & 93.5 & 7 & 0.064815 & 0.537037 & 0.064815 \tabularnewline
[94,95[ & 94.5 & 3 & 0.027778 & 0.564815 & 0.027778 \tabularnewline
[95,96[ & 95.5 & 3 & 0.027778 & 0.592593 & 0.027778 \tabularnewline
[96,97[ & 96.5 & 6 & 0.055556 & 0.648148 & 0.055556 \tabularnewline
[97,98[ & 97.5 & 3 & 0.027778 & 0.675926 & 0.027778 \tabularnewline
[98,99[ & 98.5 & 8 & 0.074074 & 0.75 & 0.074074 \tabularnewline
[99,100[ & 99.5 & 7 & 0.064815 & 0.814815 & 0.064815 \tabularnewline
[100,101] & 100.5 & 20 & 0.185185 & 1 & 0.185185 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281093&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][85,86[[/C][C]85.5[/C][C]4[/C][C]0.037037[/C][C]0.037037[/C][C]0.037037[/C][/ROW]
[ROW][C][86,87[[/C][C]86.5[/C][C]9[/C][C]0.083333[/C][C]0.12037[/C][C]0.083333[/C][/ROW]
[ROW][C][87,88[[/C][C]87.5[/C][C]9[/C][C]0.083333[/C][C]0.203704[/C][C]0.083333[/C][/ROW]
[ROW][C][88,89[[/C][C]88.5[/C][C]2[/C][C]0.018519[/C][C]0.222222[/C][C]0.018519[/C][/ROW]
[ROW][C][89,90[[/C][C]89.5[/C][C]1[/C][C]0.009259[/C][C]0.231481[/C][C]0.009259[/C][/ROW]
[ROW][C][90,91[[/C][C]90.5[/C][C]3[/C][C]0.027778[/C][C]0.259259[/C][C]0.027778[/C][/ROW]
[ROW][C][91,92[[/C][C]91.5[/C][C]13[/C][C]0.12037[/C][C]0.37963[/C][C]0.12037[/C][/ROW]
[ROW][C][92,93[[/C][C]92.5[/C][C]10[/C][C]0.092593[/C][C]0.472222[/C][C]0.092593[/C][/ROW]
[ROW][C][93,94[[/C][C]93.5[/C][C]7[/C][C]0.064815[/C][C]0.537037[/C][C]0.064815[/C][/ROW]
[ROW][C][94,95[[/C][C]94.5[/C][C]3[/C][C]0.027778[/C][C]0.564815[/C][C]0.027778[/C][/ROW]
[ROW][C][95,96[[/C][C]95.5[/C][C]3[/C][C]0.027778[/C][C]0.592593[/C][C]0.027778[/C][/ROW]
[ROW][C][96,97[[/C][C]96.5[/C][C]6[/C][C]0.055556[/C][C]0.648148[/C][C]0.055556[/C][/ROW]
[ROW][C][97,98[[/C][C]97.5[/C][C]3[/C][C]0.027778[/C][C]0.675926[/C][C]0.027778[/C][/ROW]
[ROW][C][98,99[[/C][C]98.5[/C][C]8[/C][C]0.074074[/C][C]0.75[/C][C]0.074074[/C][/ROW]
[ROW][C][99,100[[/C][C]99.5[/C][C]7[/C][C]0.064815[/C][C]0.814815[/C][C]0.064815[/C][/ROW]
[ROW][C][100,101][/C][C]100.5[/C][C]20[/C][C]0.185185[/C][C]1[/C][C]0.185185[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281093&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281093&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
[85,86[85.540.0370370.0370370.037037
[86,87[86.590.0833330.120370.083333
[87,88[87.590.0833330.2037040.083333
[88,89[88.520.0185190.2222220.018519
[89,90[89.510.0092590.2314810.009259
[90,91[90.530.0277780.2592590.027778
[91,92[91.5130.120370.379630.12037
[92,93[92.5100.0925930.4722220.092593
[93,94[93.570.0648150.5370370.064815
[94,95[94.530.0277780.5648150.027778
[95,96[95.530.0277780.5925930.027778
[96,97[96.560.0555560.6481480.055556
[97,98[97.530.0277780.6759260.027778
[98,99[98.580.0740740.750.074074
[99,100[99.570.0648150.8148150.064815
[100,101]100.5200.18518510.185185



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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '5'
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')
}