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Author*The author of this computation has been verified*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationWed, 13 Dec 2017 10:15:58 +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/2017/Dec/13/t1513156649froidjdnqdej9hs.htm/, Retrieved Wed, 15 May 2024 17:56:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309226, Retrieved Wed, 15 May 2024 17:56:48 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [Pearson correlati...] [2017-12-13 09:15:58] [09ca0998dffcdc3bb8b8a63ab2cdd9f2] [Current]
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Dataseries X:
8485
1500000
103833
15000
9964
10000
15000
18896
5000
30657
20335
3105
34965
25302
7400
17232
13681
16000
10879
36000
434084
33837
3370
12101
11242
90215
326
228
14034
37700
18491
12913
100000
0
3500
600
17859
50
52000
31730
7551
0
17000
12000
52000
0
1126
39466
113
21000
27368
20200
50000
18450
9520
8241
101647
37782
25109
46500
0
16112
80000
526269
70745
20516
400
24000
20000
1025
70000
3084506
9206
10882
29828
1000
18269
710
32031
68770
12759
10659
7495
19951
6333
2056743
73467
16000
10393
2662
23300
0
0
25986
6541
9964
6971
6986
5000
9501
3152
23009
68120
61092
9841
10000
41214
377
2000
10000
28467
12545
12500
5000
2188
25000
250
18127
5256
37000
18013
17504
2803
28074
637957
12804
10000
27607
18736
337
15869
0
4123
85291
16340
9133
2676
14634
0
10000
3030
9695
4000
2960
54938
634746
7164
100
1451529
55000
23747
4200
127800
53779
3000
9573
16897
500
15463
13650
20833
22376
26253
107441
16725
66711
517
13986
18352
70000
1100
59343
14548
7214
78780
20400
11492
2998
37240
8240
11322
716360
26059
9666
10000
33100
24573
4700
50400
25217
22692
1921
33000
5000
80000
2000
46297
9964
4435
104600
9950
30000
5000
15000
179895
14164
6620
15000
25150
8537
50
14768
9187
176
21507
3643
68350
13671
26771
30540
3811
111680
22465
59450
10760
19739
300
15626
30000
8000
41691
1301
19082
10339
149066
206278
14879
23609
99014
20000
57675
9517
275000
20000
91500
40810
12150
4489
13067
0
2375691
800
6743
6200
11332
14795
220000
13000
5000
19940
10000
78320
350
13618
60000
7000
2000
8510
839804
24000
18782
5590
206514
9862
14051
Dataseries Y:
24
0
10
4
45
2
4
9
3
10
7
40
5
4
8
6
1
2
0
3
44
5
0
14
37
3
4
0
8
11
6
4
26
0
37
5
4
39
8
3
5
5
45
2
15
5
4
7
0
7
19
1
3
4
57
4
47
8
42
0
52
5
5
29
5
10
10
7
79
38
5
43
3
60
7
79
8
3
4
9
4
9
2
0
2
26
40
35
79
5
0
10
10
2
4
44
41
43
6
5
55
11
3
0
5
76
0
2
20
0
15
5
18
20
6
23
0
0
14
12
3
0
6
17
47
32
0
0
0
3
0
4
2
0
6
1
8
5
5
3
9
45
8
5
4
47
10
32
46
5
5
9
34
0
3
38
0
2
30
3
70
5
4
22
54
3
3
50
50
15
9
5
40
5
7
5
6
24
0
3
45
45
6
5
44
4
50
30
30
10
3
7
50
7
7
79
55
45
2
14
17
3
0
7
30
10
11
7
5
5
4
0
0
15
0
4
6
7
3
3
6
4
3
19
7
6
28
4
5
10
3
8
9
6
13
10
9
60
30
12
3
4
0
30
7
2
9
0
0
15
65
20
8
22
4
6
24
10
3
9
9
0
4
10
8
3
0
8
48
11
9
27
10
9
30




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time5 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309226&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]5 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309226&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309226&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean76916.0414.7236363636364
Biased Variance91485622617.8057324.461804958678
Biased Standard Deviation302465.90323176218.0128233477897
Covariance1287638.8249635
Correlation0.235479832453684
Determination0.0554507514924153
T-Test4.0033424182316
p-value (2 sided)8.05392081326326e-05
p-value (1 sided)4.02696040663163e-05
95% CI of Correlation[0.120553719505989, 0.344177250570083]
Degrees of Freedom273
Number of Observations275

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 76916.04 & 14.7236363636364 \tabularnewline
Biased Variance & 91485622617.8057 & 324.461804958678 \tabularnewline
Biased Standard Deviation & 302465.903231762 & 18.0128233477897 \tabularnewline
Covariance & 1287638.8249635 \tabularnewline
Correlation & 0.235479832453684 \tabularnewline
Determination & 0.0554507514924153 \tabularnewline
T-Test & 4.0033424182316 \tabularnewline
p-value (2 sided) & 8.05392081326326e-05 \tabularnewline
p-value (1 sided) & 4.02696040663163e-05 \tabularnewline
95% CI of Correlation & [0.120553719505989, 0.344177250570083] \tabularnewline
Degrees of Freedom & 273 \tabularnewline
Number of Observations & 275 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309226&T=1

[TABLE]
[ROW][C]Pearson Product Moment Correlation - Ungrouped Data[/C][/ROW]
[ROW][C]Statistic[/C][C]Variable X[/C][C]Variable Y[/C][/ROW]
[ROW][C]Mean[/C][C]76916.04[/C][C]14.7236363636364[/C][/ROW]
[ROW][C]Biased Variance[/C][C]91485622617.8057[/C][C]324.461804958678[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]302465.903231762[/C][C]18.0128233477897[/C][/ROW]
[ROW][C]Covariance[/C][C]1287638.8249635[/C][/ROW]
[ROW][C]Correlation[/C][C]0.235479832453684[/C][/ROW]
[ROW][C]Determination[/C][C]0.0554507514924153[/C][/ROW]
[ROW][C]T-Test[/C][C]4.0033424182316[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]8.05392081326326e-05[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]4.02696040663163e-05[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][0.120553719505989, 0.344177250570083][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]273[/C][/ROW]
[ROW][C]Number of Observations[/C][C]275[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309226&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309226&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean76916.0414.7236363636364
Biased Variance91485622617.8057324.461804958678
Biased Standard Deviation302465.90323176218.0128233477897
Covariance1287638.8249635
Correlation0.235479832453684
Determination0.0554507514924153
T-Test4.0033424182316
p-value (2 sided)8.05392081326326e-05
p-value (1 sided)4.02696040663163e-05
95% CI of Correlation[0.120553719505989, 0.344177250570083]
Degrees of Freedom273
Number of Observations275







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 36977, p-value < 2.2e-16
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 178.08, p-value < 2.2e-16
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 77.999, p-value < 2.2e-16
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.889, p-value < 2.2e-16

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 36977, p-value < 2.2e-16
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 178.08, p-value < 2.2e-16
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 77.999, p-value < 2.2e-16
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.889, p-value < 2.2e-16
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=309226&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 36977, p-value < 2.2e-16
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 178.08, p-value < 2.2e-16
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 77.999, p-value < 2.2e-16
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.889, p-value < 2.2e-16
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309226&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309226&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 36977, p-value < 2.2e-16
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 178.08, p-value < 2.2e-16
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 77.999, p-value < 2.2e-16
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.889, p-value < 2.2e-16



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
library(psychometric)
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$estimate)[1,1]
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Variable X',1,TRUE)
a<-table.element(a,'Variable Y',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,mean(x))
a<-table.element(a,mean(y))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Biased Variance',header=TRUE)
a<-table.element(a,varx)
a<-table.element(a,vary)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Biased Standard Deviation',header=TRUE)
a<-table.element(a,sqrt(varx))
a<-table.element(a,sqrt(vary))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Covariance',header=TRUE)
a<-table.element(a,cov(x,y),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',header=TRUE)
a<-table.element(a,cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Determination',header=TRUE)
a<-table.element(a,cxy*cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-Test',header=TRUE)
a<-table.element(a,as.matrix(corxy$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,'95% CI of Correlation',header=TRUE)
a<-table.element(a,paste('[',CIr(r=cxy, n = lx, level = .95)[1],', ', CIr(r=cxy, n = lx, level = .95)[2],']',sep=''),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')
qqPlot(x,main='QQplot of variable x')
dev.off()
bitmap(file='test3.png')
qqPlot(y,main='QQplot of variable y')
dev.off()