Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationSun, 07 Dec 2014 14:21:49 +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/07/t1417962122wbqfdhhp3rtfs23.htm/, Retrieved Thu, 16 May 2024 12:03:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263787, Retrieved Thu, 16 May 2024 12:03:01 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared and McNemar Tests] [] [2010-11-16 14:33:59] [b98453cac15ba1066b407e146608df68]
- RMPD    [Pearson Correlation] [LKMLK] [2014-12-07 14:21:49] [ccc8d5d8fda28a28a4ef088d048ade85] [Current]
- RMPD      [Bivariate Kernel Density Estimation] [LKLMK] [2014-12-07 14:29:03] [9378e2688aa9dcfd1390615d31e9d404]
- R P         [Bivariate Kernel Density Estimation] [JMOKJMO] [2014-12-07 14:30:39] [9378e2688aa9dcfd1390615d31e9d404]
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Dataseries X:
Female
Female
Male
Female
Male
Male
Male
Female
Male
Male
Male
Male
Male
Male
Female
Female
Female
Male
Female
Male
Female
Male
Male
Female
Male
Male
Male
Male
Female
Male
Female
Female
Female
Male
Male
Male
Male
Male
Female
Male
Male
Female
Male
Male
Male
Male
Male
Female
Male
Male
Female
Male
Male
Male
Male
Male
Male
Male
Female
Male
Female
Male
Male
Female
Female
Male
Female
Male
Female
Male
Male
Female
Female
Female
Female
Male
Male
Female
Male
Female
Male
Female
Female
Male
Female
Female
Female
Male
Female
Male
Male
Female
Female
Female
Male
Male
Male
Female
Male
Female
Male
Male
Male
Male
Male
Female
Male
Male
Male
Female
Female
Female
Female
Female
Female
Male
Male
Male
Male
Male
Female
Male
Male
Female
Male
Female
Female
Male
Male
Male
Male
Male
Male
Male
Male
Female
Male
Male
Male
Male
Male
Male
Female
Male
Male
Male
Male
Male
Female
Female
Female
Male
Female
Female
Female
Male
Female
Male
Male
Female
Male
Male
Male
Female
Female
Female
Female
Male
Female
Male
Female
Male
Female
Male
Female
Female
Male
Female
Male
Male
Male
Male
Male
Female
Male
Female
Female
Female
Male
Female
Male
Female
Female
Female
Female
Male
Male
Male
Male
Female
Female
Male
Female
Female
Female
Female
Male
Male
Female
Female
Male
Female
Male
Male
Male
Female
Male
Male
Male
Female
Female
Female
Male
Male
Female
Male
Male
Female
Female
Female
Male
Male
Female
Female
Female
Male
Male
Female
Female
Female
Male
Male
Male
Male
Female
Male
Male
Male
Female
Female
Male
Female
Male
Male
Male
Female
Male
Female
Male
Male
Female
Male
Female
Male
Female
Male
Female
Female
Male
Male
Female
Male
Male
Female
Male
Female
Female
Male
Male
Female
Male
Female
Female
Male
Female
Female
Male
Male
Male
Female
Male
Male
Male
Male
Female
Male
Female
Female
Male
Female
Male
Female
Female
Male
Female
Male
Male
Female
Female
Female
Male
Female
Male
Male
Male
Male
Female
Male
Female
Male
Female
Female
Female
Female
Female
Female
Male
Male
Male
Female
Female
Female
Female
Female
Male
Male
Male
Male
Female
Male
Female
Male
Male
Female
Male
Female
Female
Female
Female
Female
Female
Male
Female
Female
Male
Male
Male
Male
Female
Male
Male
Female
Female
Female
Female
Male
Female
Female
Female
Female
Female
Female
Male
Male
Male
Female
Female
Male
Female
Male
Male
Male
Male
Male
Female
Female
Female
Female
Female
Male
Female
Female
Male
Female
Female
Male
Female
Male
Male
Female
Male
Female
Male
Female
Male
Male
Male
Female
Male
Male
Female
Male
Male
Male
Male
Female
Male
Female
Female
Male
Female
Male
Male
Female
Female
Male
Male
Male
Male
Female
Male
Male
Male
Male
Female
Female
Male
Female
Male
Male
Female
Male
Female
Male
Female
Female
Male
Male
Male
Male
Female
Female
Male
Female
Male
Female
Male
Male
Male
Male
Male
Male
Male
Male
Female
Male
Female
Female
Male
Male
Male
Male
Male
Male
Male
Female
Male
Male
Male
Female
Male
Male
Male
Male
Female
Male
Male
Female
Female
Male
Male
Male
Male
Female
Male
Female
Male
Male
Female
Female
Male
Male
Male
Male
Male
Female
Male
Male
Male
Female
Female
Male
Female
Male
Dataseries Y:
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
NA
NA
NA
NA
53
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263787&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263787&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263787&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'Sir Maurice George Kendall' @ kendall.wessa.net



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
x <- x[!is.na(y)]
y <- y[!is.na(y)]
y <- y[!is.na(x)]
x <- x[!is.na(x)]
bitmap(file='test1.png')
histx <- hist(x, plot=FALSE)
histy <- hist(y, plot=FALSE)
maxcounts <- max(c(histx$counts, histx$counts))
xrange <- c(min(x),max(x))
yrange <- c(min(y),max(y))
nf <- layout(matrix(c(2,0,1,3),2,2,byrow=TRUE), c(3,1), c(1,3), TRUE)
par(mar=c(4,4,1,1))
plot(x, y, xlim=xrange, ylim=yrange, xlab=xlab, ylab=ylab, sub=main)
par(mar=c(0,4,1,1))
barplot(histx$counts, axes=FALSE, ylim=c(0, maxcounts), space=0)
par(mar=c(4,0,1,1))
barplot(histy$counts, axes=FALSE, xlim=c(0, maxcounts), space=0, horiz=TRUE)
dev.off()
lx = length(x)
makebiased = (lx-1)/lx
varx = var(x)*makebiased
vary = var(y)*makebiased
corxy <- cor.test(x,y,method='pearson', na.rm = T)
cxy <- as.matrix(corxy$estimate)[1,1]
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Variable X',1,TRUE)
a<-table.element(a,'Variable Y',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm','Mean',''),header=TRUE)
a<-table.element(a,mean(x))
a<-table.element(a,mean(y))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased.htm','Biased Variance',''),header=TRUE)
a<-table.element(a,varx)
a<-table.element(a,vary)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased1.htm','Biased Standard Deviation',''),header=TRUE)
a<-table.element(a,sqrt(varx))
a<-table.element(a,sqrt(vary))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('covariance.htm','Covariance',''),header=TRUE)
a<-table.element(a,cov(x,y),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('pearson_correlation.htm','Correlation',''),header=TRUE)
a<-table.element(a,cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('coeff_of_determination.htm','Determination',''),header=TRUE)
a<-table.element(a,cxy*cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ttest_statistic.htm','T-Test',''),header=TRUE)
a<-table.element(a,as.matrix(corxy$statistic)[1,1],2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (2 sided)',header=TRUE)
a<-table.element(a,(p2 <- as.matrix(corxy$p.value)[1,1]),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (1 sided)',header=TRUE)
a<-table.element(a,p2/2,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degrees of Freedom',header=TRUE)
a<-table.element(a,lx-2,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of Observations',header=TRUE)
a<-table.element(a,lx,2)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
library(moments)
library(nortest)
jarque.x <- jarque.test(x)
jarque.y <- jarque.test(y)
if(lx>7) {
ad.x <- ad.test(x)
ad.y <- ad.test(y)
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Normality Tests',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('jarque.x'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('jarque.y'),'
',sep=''))
a<-table.row.end(a)
if(lx>7) {
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('ad.x'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('ad.y'),'
',sep=''))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
library(car)
bitmap(file='test2.png')
qq.plot(x,main='QQplot of variable x')
dev.off()
bitmap(file='test3.png')
qq.plot(y,main='QQplot of variable y')
dev.off()