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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 computationFri, 11 Dec 2015 12:50:07 +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/t1449839404o5hvmmtzfa530lw.htm/, Retrieved Thu, 16 May 2024 21:00:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=285936, Retrieved Thu, 16 May 2024 21:00:30 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Pearson Correlation] [] [2015-09-15 13:18:14] [32b17a345b130fdf5cc88718ed94a974]
- R  D    [Pearson Correlation] [] [2015-12-11 12:50:07] [b4712dc468fc78917cdf7a5954f8e48b] [Current]
-           [Pearson Correlation] [] [2015-12-13 17:24:13] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
1
4
6
1
8
3
8
7
7
4
6
2
5
2
5
Dataseries Y:
5
5
1
7
2
4
1
2
2
5
3
7
6
9
4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285936&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285936&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285936&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 time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean4.64.2
Biased Variance5.445.36
Biased Standard Deviation2.332380757938122.31516738055805
Covariance-4.84285714285714
Correlation-0.837060001961168
Determination0.700669446883231
T-Test-5.51636179736035
p-value (2 sided)9.93495201726672e-05
p-value (1 sided)4.96747600863336e-05
Degrees of Freedom13
Number of Observations15

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 4.6 & 4.2 \tabularnewline
Biased Variance & 5.44 & 5.36 \tabularnewline
Biased Standard Deviation & 2.33238075793812 & 2.31516738055805 \tabularnewline
Covariance & -4.84285714285714 \tabularnewline
Correlation & -0.837060001961168 \tabularnewline
Determination & 0.700669446883231 \tabularnewline
T-Test & -5.51636179736035 \tabularnewline
p-value (2 sided) & 9.93495201726672e-05 \tabularnewline
p-value (1 sided) & 4.96747600863336e-05 \tabularnewline
Degrees of Freedom & 13 \tabularnewline
Number of Observations & 15 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285936&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]4.6[/C][C]4.2[/C][/ROW]
[ROW][C]Biased Variance[/C][C]5.44[/C][C]5.36[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]2.33238075793812[/C][C]2.31516738055805[/C][/ROW]
[ROW][C]Covariance[/C][C]-4.84285714285714[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.837060001961168[/C][/ROW]
[ROW][C]Determination[/C][C]0.700669446883231[/C][/ROW]
[ROW][C]T-Test[/C][C]-5.51636179736035[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]9.93495201726672e-05[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]4.96747600863336e-05[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]13[/C][/ROW]
[ROW][C]Number of Observations[/C][C]15[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285936&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285936&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
Mean4.64.2
Biased Variance5.445.36
Biased Standard Deviation2.332380757938122.31516738055805
Covariance-4.84285714285714
Correlation-0.837060001961168
Determination0.700669446883231
T-Test-5.51636179736035
p-value (2 sided)9.93495201726672e-05
p-value (1 sided)4.96747600863336e-05
Degrees of Freedom13
Number of Observations15







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 1.0121, p-value = 0.6029
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.6843, p-value = 0.7102
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.31136, p-value = 0.5144
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.30391, p-value = 0.5284

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 1.0121, p-value = 0.6029
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.6843, p-value = 0.7102
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.31136, p-value = 0.5144
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.30391, p-value = 0.5284
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=285936&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 1.0121, p-value = 0.6029
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.6843, p-value = 0.7102
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.31136, p-value = 0.5144
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.30391, p-value = 0.5284
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=285936&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285936&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 = 1.0121, p-value = 0.6029
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.6843, p-value = 0.7102
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.31136, p-value = 0.5144
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.30391, p-value = 0.5284



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()