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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 computationMon, 11 Jan 2016 10:08:31 +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/2016/Jan/11/t1452506955mwp1a7tfeko08ap.htm/, Retrieved Tue, 07 May 2024 07:33:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=289305, Retrieved Tue, 07 May 2024 07:33:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [] [2016-01-11 10:08:31] [5b79fb4dd174cfd3d35aebad5c575e80] [Current]
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Dataseries X:
0.7923
-2.468
-2.996
3.119
0.04315
0.731
2.45
2.119
-1.429
-1.644
-3.065
-1.461
1.141
1.329
0.3396
0.8429
2.225
-1.924
0.4999
-0.6433
Dataseries Y:
3.2
NA
3.0
NA
3.7
NA
3.6
NA
3.8
NA
3.7
NA
2.8
NA
4.3
NA
3.6
NA
3.3
NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289305&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289305&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289305&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'Gertrude Mary Cox' @ cox.wessa.net







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean9.50000000000318e-053.5
Biased Variance3.3662117292250.17
Biased Standard Deviation1.834723883647070.412310562561766
Covariance0.00752666666666666
Correlation0.00895467889549833
Determination8.01862741214832e-05
T-Test0.0253286722077043
p-value (2 sided)0.98041321055814
p-value (1 sided)0.49020660527907
95% CI of Correlation[-0.624190872892284, 0.635000780529595]
Degrees of Freedom8
Number of Observations10

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 9.50000000000318e-05 & 3.5 \tabularnewline
Biased Variance & 3.366211729225 & 0.17 \tabularnewline
Biased Standard Deviation & 1.83472388364707 & 0.412310562561766 \tabularnewline
Covariance & 0.00752666666666666 \tabularnewline
Correlation & 0.00895467889549833 \tabularnewline
Determination & 8.01862741214832e-05 \tabularnewline
T-Test & 0.0253286722077043 \tabularnewline
p-value (2 sided) & 0.98041321055814 \tabularnewline
p-value (1 sided) & 0.49020660527907 \tabularnewline
95% CI of Correlation & [-0.624190872892284, 0.635000780529595] \tabularnewline
Degrees of Freedom & 8 \tabularnewline
Number of Observations & 10 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289305&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]9.50000000000318e-05[/C][C]3.5[/C][/ROW]
[ROW][C]Biased Variance[/C][C]3.366211729225[/C][C]0.17[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]1.83472388364707[/C][C]0.412310562561766[/C][/ROW]
[ROW][C]Covariance[/C][C]0.00752666666666666[/C][/ROW]
[ROW][C]Correlation[/C][C]0.00895467889549833[/C][/ROW]
[ROW][C]Determination[/C][C]8.01862741214832e-05[/C][/ROW]
[ROW][C]T-Test[/C][C]0.0253286722077043[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.98041321055814[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.49020660527907[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.624190872892284, 0.635000780529595][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]8[/C][/ROW]
[ROW][C]Number of Observations[/C][C]10[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289305&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289305&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
Mean9.50000000000318e-053.5
Biased Variance3.3662117292250.17
Biased Standard Deviation1.834723883647070.412310562561766
Covariance0.00752666666666666
Correlation0.00895467889549833
Determination8.01862741214832e-05
T-Test0.0253286722077043
p-value (2 sided)0.98041321055814
p-value (1 sided)0.49020660527907
95% CI of Correlation[-0.624190872892284, 0.635000780529595]
Degrees of Freedom8
Number of Observations10







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 0.7656, p-value = 0.6819
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.098936, p-value = 0.9517
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.39852, p-value = 0.2959
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.26416, p-value = 0.6127

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 0.7656, p-value = 0.6819
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.098936, p-value = 0.9517
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.39852, p-value = 0.2959
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.26416, p-value = 0.6127
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=289305&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 0.7656, p-value = 0.6819
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.098936, p-value = 0.9517
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.39852, p-value = 0.2959
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.26416, p-value = 0.6127
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=289305&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289305&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 = 0.7656, p-value = 0.6819
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 0.098936, p-value = 0.9517
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.39852, p-value = 0.2959
> ad.y
	Anderson-Darling normality test
data:  y
A = 0.26416, p-value = 0.6127



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$estimate)[1,1]
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Variable X',1,TRUE)
a<-table.element(a,'Variable Y',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm','Mean',''),header=TRUE)
a<-table.element(a,mean(x))
a<-table.element(a,mean(y))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased.htm','Biased Variance',''),header=TRUE)
a<-table.element(a,varx)
a<-table.element(a,vary)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased1.htm','Biased Standard Deviation',''),header=TRUE)
a<-table.element(a,sqrt(varx))
a<-table.element(a,sqrt(vary))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('covariance.htm','Covariance',''),header=TRUE)
a<-table.element(a,cov(x,y),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('pearson_correlation.htm','Correlation',''),header=TRUE)
a<-table.element(a,cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('coeff_of_determination.htm','Determination',''),header=TRUE)
a<-table.element(a,cxy*cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ttest_statistic.htm','T-Test',''),header=TRUE)
a<-table.element(a,as.matrix(corxy$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()