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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSun, 14 Dec 2014 17:18:01 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/14/t1418577498kby9c7vvoozpy83.htm/, Retrieved Thu, 16 May 2024 16:37:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267761, Retrieved Thu, 16 May 2024 16:37:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Stem-and-leaf Plot] [] [2013-10-01 09:27:37] [0307e7a6407eb638caabc417e3a6b260]
- RM D  [Stem-and-leaf Plot] [Stem-and-leaf Plot] [2014-09-30 14:09:08] [fa1b8827d7de91b8b87087311d3d9fa1]
- R       [Stem-and-leaf Plot] [] [2014-10-01 15:47:51] [fa1b8827d7de91b8b87087311d3d9fa1]
- RMPD        [Histogram] [] [2014-12-14 17:18:01] [2b74e5be20a95dee0bfccc444f4c1798] [Current]
- R             [Histogram] [] [2014-12-14 18:08:04] [fa1b8827d7de91b8b87087311d3d9fa1]
- RM D          [Mean versus Median] [] [2014-12-14 18:11:20] [fa1b8827d7de91b8b87087311d3d9fa1]
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Dataseries X:
50
62
54
71
54
65
73
52
84
42
66
65
78
73
75
72
66
70
61
81
71
69
71
72
68
70
68
61
67
76
70
60
72
69
71
62
70
64
58
76
52
59
68
76
65
67
59
69
76
63
75
63
60
73
63
70
75
66
63
63
64
70
75
61
60
62
73
61
66
64
59
64
60
56
78
53
67
59
66
68
71
66
73
72
71
59
64
66
78
68
73
62
65
68
65
60
71
65
68
64
74
69
76
68
72
67
63
59
73
66
62
69
66
51
56
67
69
57
56
55
63
67
65
47
76
64
68
64
65
71
63
60
68
72
70
61
61
62
71
71
51
56
70
73
76
68
48
52
60
59
57
79
60
60
59
62
59
61
71
57
66
63
69
58
59
48
66
73
67
61
68
75
62
69
58
60
74
55
62
63
69
58
58
68
72
62
62
65
69
66
72
62
75
58
66
55
47
72
62
64
64
19
50
68
70
79
69
71
48
73
74
66
71
74
78
75
53
60
70
69
65
78
78
59
72
70
63
63
71
74
67
66
62
80
73
67
61
73
74
32
69
69
84
64
58
59
78
57
60
68
68
73
69
67
60
65
66
74
81
72
55
49
74
53
64
65
57
51
80
67
70
74
75
70
69
65
55
71
65
69
48
69
68
74
67
65
63
74
39
68
69
68
63
67
70
68
70
78
59
62
75
74
73
62
69
67
73
52
61
53
63
78
65
77
69
68
76
63
41
76
67
69
59
73
72
52
65
63
78
56
68
56
64
68
75
67
55
73
66
75
77
65
75
57
61
71
72
62
66
66
63
60
64
74
59
71
69
63
73
55
77
70
64
78
60
66
77
68
78
68
60
65
64
69
72
50
72
71
80
74
64
69
76
75
79
73
60
76
55
53
62
69
78
68
67
75
59
73
70
59
64
63
67
58
71
79
53
76
66
64
57
67
72
58
74
57
62
74
54
62
66
64
74
71
66
66
63
65
70
66
66
78
77
72
65
67
72
58
84
67
84
58
63
75
72
58
69
54
58
67
77
80
67
75
71
72
75
79
76
72
81
52
76
60
72
77
64
67
72
79
40
71
73
75
70
66
66
73
74
58
51
75
70
50
64
77
71




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=267761&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=267761&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267761&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
[15,20[17.510.0020530.0020530.000411
[20,25[22.5000.0020530
[25,30[27.5000.0020530
[30,35[32.510.0020530.0041070.000411
[35,40[37.510.0020530.006160.000411
[40,45[42.530.006160.012320.001232
[45,50[47.570.0143740.0266940.002875
[50,55[52.5240.0492810.0759750.009856
[55,60[57.5530.108830.1848050.021766
[60,65[62.5930.1909650.375770.038193
[65,70[67.51260.2587270.6344970.051745
[70,75[72.51060.2176590.8521560.043532
[75,80[77.5610.1252570.9774130.025051
[80,85]82.5110.02258710.004517

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[15,20[ & 17.5 & 1 & 0.002053 & 0.002053 & 0.000411 \tabularnewline
[20,25[ & 22.5 & 0 & 0 & 0.002053 & 0 \tabularnewline
[25,30[ & 27.5 & 0 & 0 & 0.002053 & 0 \tabularnewline
[30,35[ & 32.5 & 1 & 0.002053 & 0.004107 & 0.000411 \tabularnewline
[35,40[ & 37.5 & 1 & 0.002053 & 0.00616 & 0.000411 \tabularnewline
[40,45[ & 42.5 & 3 & 0.00616 & 0.01232 & 0.001232 \tabularnewline
[45,50[ & 47.5 & 7 & 0.014374 & 0.026694 & 0.002875 \tabularnewline
[50,55[ & 52.5 & 24 & 0.049281 & 0.075975 & 0.009856 \tabularnewline
[55,60[ & 57.5 & 53 & 0.10883 & 0.184805 & 0.021766 \tabularnewline
[60,65[ & 62.5 & 93 & 0.190965 & 0.37577 & 0.038193 \tabularnewline
[65,70[ & 67.5 & 126 & 0.258727 & 0.634497 & 0.051745 \tabularnewline
[70,75[ & 72.5 & 106 & 0.217659 & 0.852156 & 0.043532 \tabularnewline
[75,80[ & 77.5 & 61 & 0.125257 & 0.977413 & 0.025051 \tabularnewline
[80,85] & 82.5 & 11 & 0.022587 & 1 & 0.004517 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267761&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][15,20[[/C][C]17.5[/C][C]1[/C][C]0.002053[/C][C]0.002053[/C][C]0.000411[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]0[/C][C]0[/C][C]0.002053[/C][C]0[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]0[/C][C]0[/C][C]0.002053[/C][C]0[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]1[/C][C]0.002053[/C][C]0.004107[/C][C]0.000411[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]1[/C][C]0.002053[/C][C]0.00616[/C][C]0.000411[/C][/ROW]
[ROW][C][40,45[[/C][C]42.5[/C][C]3[/C][C]0.00616[/C][C]0.01232[/C][C]0.001232[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]7[/C][C]0.014374[/C][C]0.026694[/C][C]0.002875[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]24[/C][C]0.049281[/C][C]0.075975[/C][C]0.009856[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]53[/C][C]0.10883[/C][C]0.184805[/C][C]0.021766[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]93[/C][C]0.190965[/C][C]0.37577[/C][C]0.038193[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]126[/C][C]0.258727[/C][C]0.634497[/C][C]0.051745[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]106[/C][C]0.217659[/C][C]0.852156[/C][C]0.043532[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]61[/C][C]0.125257[/C][C]0.977413[/C][C]0.025051[/C][/ROW]
[ROW][C][80,85][/C][C]82.5[/C][C]11[/C][C]0.022587[/C][C]1[/C][C]0.004517[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267761&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267761&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
[15,20[17.510.0020530.0020530.000411
[20,25[22.5000.0020530
[25,30[27.5000.0020530
[30,35[32.510.0020530.0041070.000411
[35,40[37.510.0020530.006160.000411
[40,45[42.530.006160.012320.001232
[45,50[47.570.0143740.0266940.002875
[50,55[52.5240.0492810.0759750.009856
[55,60[57.5530.108830.1848050.021766
[60,65[62.5930.1909650.375770.038193
[65,70[67.51260.2587270.6344970.051745
[70,75[72.51060.2176590.8521560.043532
[75,80[77.5610.1252570.9774130.025051
[80,85]82.5110.02258710.004517



Parameters (Session):
par1 = 1 ; par2 = 90 ; par3 = 1e-08 ;
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 {
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')
}