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 computationFri, 11 Dec 2015 22:00:20 +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/2015/Dec/11/t1449871376jqjejk9x2vczynt.htm/, Retrieved Thu, 31 Oct 2024 22:53:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286043, Retrieved Thu, 31 Oct 2024 22:53:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [Hypothese 3] [2015-12-11 22:00:20] [3e2780e2cb0e47accd70a310e72f0fc9] [Current]
Feedback Forum

Post a new message
Dataseries X:
12
8
11
13
11
10
7
10
15
12
12
10
10
14
6
12
14
11
8
12
15
13
11
12
7
11
7
12
12
13
9
11
12
15
12
6
5
13
11
6
12
10
6
12
11
6
12
12
8
10
11
7
12
13
14
12
6
14
10
12
11
10
7
12
7
12
12
10
10
12
12
12
8
10
5
10
12
11
9
12
11
10
12
10
9
11
12
7
11
12
6
9
15
10
11
12
12
12
11
9
11
12
12
14
8
10
9
10
9
10
12
11
9
11
12
12
7
12
12
12
10
15
10
15
10
15
9
15
12
13
12
12
8
9
15
12
12
15
11
12
6
14
12
12
12
11
12
12
12
12
8
8
12
12
11
10
11
12
13
12
12
10
10
11
8
12
9
12
9
11
15
8
8
11
11
11
13
7
12
8
8
4
11
10
7
12
11
9
10
8
8
11
12
10
10
12
8
11
8
10
14
9
9
10
13
12
13
8
3
8
12
11
9
12
12
12
10
13
9
12
11
14
11
9
12
8
15
12
14
12
9
9
13
13
15
11
7
10
11
14
14
13
12
8
13
9
12
13
11
11
13
12
12
10
9
10
13
13
9
11
12
8
12
12
12
9
12
12
11
12
6
7
10
12
10
12
9
3
Dataseries Y:
4
4
5
4
4
9
8
11
4
4
6
4
8
4
4
11
4
4
6
6
4
8
5
4
9
4
7
10
4
4
7
12
7
5
8
5
4
9
7
4
4
4
4
4
7
4
7
4
4
4
4
8
4
4
4
4
7
12
4
4
4
5
15
5
10
9
8
4
5
4
9
4
10
4
4
7
5
4
4
4
4
4
4
6
10
7
4
4
7
4
8
11
6
14
5
4
8
9
4
4
5
4
5
4
4
7
10
4
5
4
4
4
6
4
8
5
4
17
4
4
8
4
7
4
4
5
7
4
4
7
11
7
4
4
4
4
4
4
6
8
23
4
8
6
4
7
4
4
4
10
6
5
5
4
4
5
5
5
5
4
6
4
4
4
9
18
6
5
4
11
4
10
6
8
8
6
8
4
4
9
9
5
4
4
15
10
9
7
9
6
4
7
4
7
4
15
4
9
4
4
28
4
4
4
5
4
4
12
4
6
6
5
4
4
4
10
7
4
7
4
4
12
5
8
6
17
4
5
4
5
5
6
4
4
4
6
8
10
4
5
4
4
4
16
7
4
4
14
5
5
5
5
7
19
16
4
4
7
9
5
14
4
16
10
5
6
4
4
4
5
4
4
5
4
4
5
8
15




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286043&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]5 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=286043&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286043&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 time5 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean10.74100719424466.2589928057554
Biased Variance5.2134982661352912.0048651726101
Biased Standard Deviation2.283308622620973.46480377115503
Covariance-1.05542425265564
Correlation-0.132928707692282
Determination0.01767004132874
T-Test-2.22815105029348
p-value (2 sided)0.0266762870097511
p-value (1 sided)0.0133381435048756
95% CI of Correlation[-0.246713570247466, -0.015528543114747]
Degrees of Freedom276
Number of Observations278

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 10.7410071942446 & 6.2589928057554 \tabularnewline
Biased Variance & 5.21349826613529 & 12.0048651726101 \tabularnewline
Biased Standard Deviation & 2.28330862262097 & 3.46480377115503 \tabularnewline
Covariance & -1.05542425265564 \tabularnewline
Correlation & -0.132928707692282 \tabularnewline
Determination & 0.01767004132874 \tabularnewline
T-Test & -2.22815105029348 \tabularnewline
p-value (2 sided) & 0.0266762870097511 \tabularnewline
p-value (1 sided) & 0.0133381435048756 \tabularnewline
95% CI of Correlation & [-0.246713570247466, -0.015528543114747] \tabularnewline
Degrees of Freedom & 276 \tabularnewline
Number of Observations & 278 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286043&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]10.7410071942446[/C][C]6.2589928057554[/C][/ROW]
[ROW][C]Biased Variance[/C][C]5.21349826613529[/C][C]12.0048651726101[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]2.28330862262097[/C][C]3.46480377115503[/C][/ROW]
[ROW][C]Covariance[/C][C]-1.05542425265564[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.132928707692282[/C][/ROW]
[ROW][C]Determination[/C][C]0.01767004132874[/C][/ROW]
[ROW][C]T-Test[/C][C]-2.22815105029348[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.0266762870097511[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0133381435048756[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.246713570247466, -0.015528543114747][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]276[/C][/ROW]
[ROW][C]Number of Observations[/C][C]278[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286043&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286043&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
Mean10.74100719424466.2589928057554
Biased Variance5.2134982661352912.0048651726101
Biased Standard Deviation2.283308622620973.46480377115503
Covariance-1.05542425265564
Correlation-0.132928707692282
Determination0.01767004132874
T-Test-2.22815105029348
p-value (2 sided)0.0266762870097511
p-value (1 sided)0.0133381435048756
95% CI of Correlation[-0.246713570247466, -0.015528543114747]
Degrees of Freedom276
Number of Observations278







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 19.636, p-value = 5.447e-05
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 1061.9, p-value < 2.2e-16
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 6.2525, p-value = 2.162e-15
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.791, p-value < 2.2e-16

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 19.636, p-value = 5.447e-05
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 1061.9, p-value < 2.2e-16
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 6.2525, p-value = 2.162e-15
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.791, p-value < 2.2e-16
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=286043&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 19.636, p-value = 5.447e-05
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 1061.9, p-value < 2.2e-16
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 6.2525, p-value = 2.162e-15
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.791, p-value < 2.2e-16
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=286043&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286043&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 = 19.636, p-value = 5.447e-05
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 1061.9, p-value < 2.2e-16
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 6.2525, p-value = 2.162e-15
> ad.y
	Anderson-Darling normality test
data:  y
A = 26.791, p-value < 2.2e-16



Parameters (Session):
par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ;
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$estimate)[1,1]
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Variable X',1,TRUE)
a<-table.element(a,'Variable Y',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm','Mean',''),header=TRUE)
a<-table.element(a,mean(x))
a<-table.element(a,mean(y))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased.htm','Biased Variance',''),header=TRUE)
a<-table.element(a,varx)
a<-table.element(a,vary)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased1.htm','Biased Standard Deviation',''),header=TRUE)
a<-table.element(a,sqrt(varx))
a<-table.element(a,sqrt(vary))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('covariance.htm','Covariance',''),header=TRUE)
a<-table.element(a,cov(x,y),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('pearson_correlation.htm','Correlation',''),header=TRUE)
a<-table.element(a,cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('coeff_of_determination.htm','Determination',''),header=TRUE)
a<-table.element(a,cxy*cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ttest_statistic.htm','T-Test',''),header=TRUE)
a<-table.element(a,as.matrix(corxy$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,'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')
qq.plot(x,main='QQplot of variable x')
dev.off()
bitmap(file='test3.png')
qq.plot(y,main='QQplot of variable y')
dev.off()