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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationSat, 10 Dec 2016 12:01:10 +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/10/t14813677179k3vby5lbjuroyq.htm/, Retrieved Mon, 06 May 2024 02:29:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298640, Retrieved Mon, 06 May 2024 02:29:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [Pearson Correlatie] [2016-12-10 11:01:10] [6fe662842930c5949e61d44eeb8a265b] [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:
13
16
17
NA
NA
16
NA
NA
NA
17
17
15
16
14
16
17
NA
NA
NA
NA
16
NA
16
NA
NA
NA
16
15
16
16
13
15
17
NA
13
17
NA
14
14
18
NA
17
13
16
15
15
NA
15
13
NA
17
NA
NA
11
14
13
NA
17
16
NA
17
16
16
16
15
12
17
14
14
16
NA
NA
NA
NA
NA
15
16
14
15
17
NA
10
NA
17
NA
20
17
18
NA
17
14
NA
17
NA
17
NA
16
18
18
16
NA
NA
15
13
NA
NA
NA
NA
NA
16
NA
NA
NA
12
NA
16
16
NA
16
14
15
14
NA
15
NA
15
16
NA
NA
NA
11
NA
18
NA
11
NA
18
NA
15
19
17
NA
14
NA
13
17
14
19
14
NA
NA
16
16
15
12
NA
17
NA
NA
18
15
18
15
NA
NA
NA
16
NA
16




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298640&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]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298640&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298640&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 time3 seconds
R ServerBig Analytics Cloud Computing Center







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean24.627450980392215.4607843137255
Biased Variance3.449442522106883.48375624759708
Biased Standard Deviation1.857267488033671.86648231912255
Covariance1.65851291011454
Correlation0.473741817484153
Determination0.224431309633189
T-Test5.37937211874121
p-value (2 sided)4.92798817366795e-07
p-value (1 sided)2.46399408683397e-07
95% CI of Correlation[0.307607030418164, 0.61184672992439]
Degrees of Freedom100
Number of Observations102

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 24.6274509803922 & 15.4607843137255 \tabularnewline
Biased Variance & 3.44944252210688 & 3.48375624759708 \tabularnewline
Biased Standard Deviation & 1.85726748803367 & 1.86648231912255 \tabularnewline
Covariance & 1.65851291011454 \tabularnewline
Correlation & 0.473741817484153 \tabularnewline
Determination & 0.224431309633189 \tabularnewline
T-Test & 5.37937211874121 \tabularnewline
p-value (2 sided) & 4.92798817366795e-07 \tabularnewline
p-value (1 sided) & 2.46399408683397e-07 \tabularnewline
95% CI of Correlation & [0.307607030418164, 0.61184672992439] \tabularnewline
Degrees of Freedom & 100 \tabularnewline
Number of Observations & 102 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298640&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]24.6274509803922[/C][C]15.4607843137255[/C][/ROW]
[ROW][C]Biased Variance[/C][C]3.44944252210688[/C][C]3.48375624759708[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]1.85726748803367[/C][C]1.86648231912255[/C][/ROW]
[ROW][C]Covariance[/C][C]1.65851291011454[/C][/ROW]
[ROW][C]Correlation[/C][C]0.473741817484153[/C][/ROW]
[ROW][C]Determination[/C][C]0.224431309633189[/C][/ROW]
[ROW][C]T-Test[/C][C]5.37937211874121[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]4.92798817366795e-07[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]2.46399408683397e-07[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][0.307607030418164, 0.61184672992439][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]100[/C][/ROW]
[ROW][C]Number of Observations[/C][C]102[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298640&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298640&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
Mean24.627450980392215.4607843137255
Biased Variance3.449442522106883.48375624759708
Biased Standard Deviation1.857267488033671.86648231912255
Covariance1.65851291011454
Correlation0.473741817484153
Determination0.224431309633189
T-Test5.37937211874121
p-value (2 sided)4.92798817366795e-07
p-value (1 sided)2.46399408683397e-07
95% CI of Correlation[0.307607030418164, 0.61184672992439]
Degrees of Freedom100
Number of Observations102







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 0.45935, p-value = 0.7948
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.4587, p-value = 0.1076
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.4172, p-value = 0.001092
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.8991, p-value = 7.032e-05

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 0.45935, p-value = 0.7948
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.4587, p-value = 0.1076
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.4172, p-value = 0.001092
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.8991, p-value = 7.032e-05
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=298640&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 0.45935, p-value = 0.7948
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.4587, p-value = 0.1076
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.4172, p-value = 0.001092
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.8991, p-value = 7.032e-05
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298640&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298640&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 = 0.45935, p-value = 0.7948
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.4587, p-value = 0.1076
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.4172, p-value = 0.001092
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.8991, p-value = 7.032e-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()