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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 computationThu, 15 Dec 2016 19:49:03 +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/2016/Dec/15/t1481827750crc7vfblh4lrekr.htm/, Retrieved Fri, 03 May 2024 05:39:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299959, Retrieved Fri, 03 May 2024 05:39:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [] [2016-12-15 18:49:03] [b2e25925e4919b0d6985405fcb461c0d] [Current]
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Dataseries X:
22
24
26
21
26
25
21
24
27
28
23
25
24
24
24
25
25
NA
25
25
24
26
26
25
26
23
24
24
25
25
24
28
27
NA
23
23
24
24
22
25
25
28
22
28
25
24
24
23
25
NA
26
25
27
26
23
25
21
22
24
25
27
24
26
21
27
22
23
24
25
24
23
28
NA
24
26
22
25
25
24
24
26
21
25
25
26
25
26
27
25
NA
20
24
26
25
25
24
26
25
28
27
25
26
26
26
NA
28
NA
21
25
25
24
24
24
23
23
24
24
25
28
23
24
23
24
25
24
23
23
25
21
22
19
24
25
21
22
23
27
NA
26
29
28
24
25
25
22
25
26
26
24
25
19
25
23
25
25
26
27
24
22
25
24
23
27
24
24
21
25
25
23
Dataseries Y:
14
19
17
17
15
20
15
19
15
15
19
NA
20
18
15
14
20
NA
16
16
16
10
19
19
16
15
18
17
19
17
NA
19
20
5
19
16
15
16
18
16
15
17
NA
20
19
7
13
16
16
NA
18
18
16
17
19
16
19
13
16
13
12
17
17
17
16
16
14
16
13
16
14
20
12
13
18
14
19
18
14
18
19
15
14
17
19
13
19
18
20
15
15
15
20
15
19
18
18
15
20
17
12
18
19
20
NA
17
15
16
18
18
14
15
12
17
14
18
17
17
20
16
14
15
18
20
17
17
17
17
15
17
18
17
20
15
16
15
18
11
15
18
20
19
14
16
15
17
18
20
17
18
15
16
11
15
18
17
16
12
19
18
15
17
19
18
19
16
16
16
14




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299959&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]4 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299959&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299959&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 time4 seconds
R ServerBig Analytics Cloud Computing Center







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean24.49367088607616.6012658227848
Biased Variance3.465149815734665.21442877743951
Biased Standard Deviation1.861491288116782.28351237733442
Covariance1.14714182052729
Correlation0.268160804753141
Determination0.071910217205852
T-Test3.47666306377609
p-value (2 sided)0.000657832431557562
p-value (1 sided)0.000328916215778781
95% CI of Correlation[0.116915839041852, 0.407249301505418]
Degrees of Freedom156
Number of Observations158

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 24.493670886076 & 16.6012658227848 \tabularnewline
Biased Variance & 3.46514981573466 & 5.21442877743951 \tabularnewline
Biased Standard Deviation & 1.86149128811678 & 2.28351237733442 \tabularnewline
Covariance & 1.14714182052729 \tabularnewline
Correlation & 0.268160804753141 \tabularnewline
Determination & 0.071910217205852 \tabularnewline
T-Test & 3.47666306377609 \tabularnewline
p-value (2 sided) & 0.000657832431557562 \tabularnewline
p-value (1 sided) & 0.000328916215778781 \tabularnewline
95% CI of Correlation & [0.116915839041852, 0.407249301505418] \tabularnewline
Degrees of Freedom & 156 \tabularnewline
Number of Observations & 158 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299959&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]24.493670886076[/C][C]16.6012658227848[/C][/ROW]
[ROW][C]Biased Variance[/C][C]3.46514981573466[/C][C]5.21442877743951[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]1.86149128811678[/C][C]2.28351237733442[/C][/ROW]
[ROW][C]Covariance[/C][C]1.14714182052729[/C][/ROW]
[ROW][C]Correlation[/C][C]0.268160804753141[/C][/ROW]
[ROW][C]Determination[/C][C]0.071910217205852[/C][/ROW]
[ROW][C]T-Test[/C][C]3.47666306377609[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.000657832431557562[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.000328916215778781[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][0.116915839041852, 0.407249301505418][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]156[/C][/ROW]
[ROW][C]Number of Observations[/C][C]158[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299959&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299959&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
Mean24.49367088607616.6012658227848
Biased Variance3.465149815734665.21442877743951
Biased Standard Deviation1.861491288116782.28351237733442
Covariance1.14714182052729
Correlation0.268160804753141
Determination0.071910217205852
T-Test3.47666306377609
p-value (2 sided)0.000657832431557562
p-value (1 sided)0.000328916215778781
95% CI of Correlation[0.116915839041852, 0.407249301505418]
Degrees of Freedom156
Number of Observations158







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 2.8706, p-value = 0.238
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 22.418, p-value = 1.355e-05
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 2.6655, p-value = 9.526e-07
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.9471, p-value = 5.519e-05

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 2.8706, p-value = 0.238
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 22.418, p-value = 1.355e-05
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 2.6655, p-value = 9.526e-07
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.9471, p-value = 5.519e-05
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=299959&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 2.8706, p-value = 0.238
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 22.418, p-value = 1.355e-05
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 2.6655, p-value = 9.526e-07
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.9471, p-value = 5.519e-05
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299959&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299959&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 = 2.8706, p-value = 0.238
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 22.418, p-value = 1.355e-05
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 2.6655, p-value = 9.526e-07
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.9471, p-value = 5.519e-05



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()