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of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 03 Dec 2014 18:42:47 +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/03/t1417632194gmxgeddv14pi3us.htm/, Retrieved Thu, 16 May 2024 21:07:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263020, Retrieved Thu, 16 May 2024 21:07:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [] [2014-10-27 22:07:41] [8f0f7d8870e334acea674e48ede2c797]
-    D    [Histogram] [Histogram] [2014-12-03 18:42:47] [310e7528d8f6aa5642dc98f4186768d1] [Current]
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Dataseries X:
26
51
57
37
67
43
52
52
43
84
67
49
70
52
58
68
62
43
56
56
74
65
63
58
57
63
53
57
51
64
53
29
54
51
58
43
51
53
54
56
61
47
39
48
50
35
30
68
49
61
67
47
56
50
43
67
62
57
41
54
45
48
61
56
41
43
53
44
66
58
46
37
51
51
56
66
45
37
59
42
38
66
34
53
49
55
49
59
40
58
60
63
56
54
52
34
69
32
48
67
58
57
42
64
58
66
26
61
52
51
55
50
60
56
63
61
52
16
46
56
52
55
50
59
60
52
44
67
52
55
37
54
72
51
48
60
50
63
33
67
46
54
59
61
33
47
69
52
55
55
41
73
51
52
50
51
60
56
56
29
66
66
73
55
64
40
46
58
43
61
51
50
52
54
66
61
80
51
56
56
56
53
47
25
47
46
50
39
51
58
35
58
60
62
63
53
46
67
59
64
38
50
48
48
47
66
47
63
58
44
51
43
55
38
56
45
50
54
57
60
55
56
49
37
43
59
46
51
58
64
53
48
51
47
59
62
62
51
64
52
67
50
54
58
56
63
31
65
71
50
57
47
54
47
57
43
41
63
63
56
51
50
22
41
59
56
66
53
42
52
54
44
62
53
50
36
76
66
62
59
47
55
58
60
44
57
45
58
51
57
30
46
51
56
58
44
14
53
42
49
44
62
30
46
56
50
54
48
55
35
55
41
59
54
66
55
45
51
47
42
53
53
41
55
55
46
63
43
65
59
39
44
60
57
67
52
52
69
46
46
53
40
70
54
77
45
60
47
50
66
60
41
53
34
51
69
60
45
58
39
51
52
49
63
44
51
52
60
53
53
52
31
51
65
51
49
61
58
62
54
52
72
50
65
53
56
63
62
66
50
45
58
52
53
68
59
58
52
45
58
70
69
71
46
58
39
46
64
67
44
54
41
68
63
57
61
39
69
64
38
59
51
59
51
65
47
50
57
21
47
51
37
67
43
58
51
40
41
58
64
64
58
50
59
55
59
58
41
56
63
77
60
58
64
47
46
62
60
50
46
44
58
56
43
54
54
56
65
66
62
58
67
25
56
53
56
59
46
49
56
76
33
49
53
58
72
51
42
69
51
54
52
59
51
67
64
58




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=263020&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=263020&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263020&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
[10,15[12.510.0020120.0020120.000402
[15,20[17.510.0020120.0040240.000402
[20,25[22.520.0040240.0080480.000805
[25,30[27.560.0120720.0201210.002414
[30,35[32.5120.0241450.0442660.004829
[35,40[37.5200.0402410.0845070.008048
[40,45[42.5450.0905430.175050.018109
[45,50[47.5600.1207240.2957750.024145
[50,55[52.51170.2354120.5311870.047082
[55,60[57.51060.213280.7444670.042656
[60,65[62.5640.1287730.8732390.025755
[65,70[67.5460.0925550.9657950.018511
[70,75[72.5110.0221330.9879280.004427
[75,80[77.540.0080480.9959760.00161
[80,85]82.520.00402410.000805

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[10,15[ & 12.5 & 1 & 0.002012 & 0.002012 & 0.000402 \tabularnewline
[15,20[ & 17.5 & 1 & 0.002012 & 0.004024 & 0.000402 \tabularnewline
[20,25[ & 22.5 & 2 & 0.004024 & 0.008048 & 0.000805 \tabularnewline
[25,30[ & 27.5 & 6 & 0.012072 & 0.020121 & 0.002414 \tabularnewline
[30,35[ & 32.5 & 12 & 0.024145 & 0.044266 & 0.004829 \tabularnewline
[35,40[ & 37.5 & 20 & 0.040241 & 0.084507 & 0.008048 \tabularnewline
[40,45[ & 42.5 & 45 & 0.090543 & 0.17505 & 0.018109 \tabularnewline
[45,50[ & 47.5 & 60 & 0.120724 & 0.295775 & 0.024145 \tabularnewline
[50,55[ & 52.5 & 117 & 0.235412 & 0.531187 & 0.047082 \tabularnewline
[55,60[ & 57.5 & 106 & 0.21328 & 0.744467 & 0.042656 \tabularnewline
[60,65[ & 62.5 & 64 & 0.128773 & 0.873239 & 0.025755 \tabularnewline
[65,70[ & 67.5 & 46 & 0.092555 & 0.965795 & 0.018511 \tabularnewline
[70,75[ & 72.5 & 11 & 0.022133 & 0.987928 & 0.004427 \tabularnewline
[75,80[ & 77.5 & 4 & 0.008048 & 0.995976 & 0.00161 \tabularnewline
[80,85] & 82.5 & 2 & 0.004024 & 1 & 0.000805 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263020&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][10,15[[/C][C]12.5[/C][C]1[/C][C]0.002012[/C][C]0.002012[/C][C]0.000402[/C][/ROW]
[ROW][C][15,20[[/C][C]17.5[/C][C]1[/C][C]0.002012[/C][C]0.004024[/C][C]0.000402[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]2[/C][C]0.004024[/C][C]0.008048[/C][C]0.000805[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]6[/C][C]0.012072[/C][C]0.020121[/C][C]0.002414[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]12[/C][C]0.024145[/C][C]0.044266[/C][C]0.004829[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]20[/C][C]0.040241[/C][C]0.084507[/C][C]0.008048[/C][/ROW]
[ROW][C][40,45[[/C][C]42.5[/C][C]45[/C][C]0.090543[/C][C]0.17505[/C][C]0.018109[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]60[/C][C]0.120724[/C][C]0.295775[/C][C]0.024145[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]117[/C][C]0.235412[/C][C]0.531187[/C][C]0.047082[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]106[/C][C]0.21328[/C][C]0.744467[/C][C]0.042656[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]64[/C][C]0.128773[/C][C]0.873239[/C][C]0.025755[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]46[/C][C]0.092555[/C][C]0.965795[/C][C]0.018511[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]11[/C][C]0.022133[/C][C]0.987928[/C][C]0.004427[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]4[/C][C]0.008048[/C][C]0.995976[/C][C]0.00161[/C][/ROW]
[ROW][C][80,85][/C][C]82.5[/C][C]2[/C][C]0.004024[/C][C]1[/C][C]0.000805[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263020&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263020&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
[10,15[12.510.0020120.0020120.000402
[15,20[17.510.0020120.0040240.000402
[20,25[22.520.0040240.0080480.000805
[25,30[27.560.0120720.0201210.002414
[30,35[32.5120.0241450.0442660.004829
[35,40[37.5200.0402410.0845070.008048
[40,45[42.5450.0905430.175050.018109
[45,50[47.5600.1207240.2957750.024145
[50,55[52.51170.2354120.5311870.047082
[55,60[57.51060.213280.7444670.042656
[60,65[62.5640.1287730.8732390.025755
[65,70[67.5460.0925550.9657950.018511
[70,75[72.5110.0221330.9879280.004427
[75,80[77.540.0080480.9959760.00161
[80,85]82.520.00402410.000805



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 {
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')
}