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Description of Statistical Computation

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, 17 Dec 2016 12:36:46 +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/17/t1481974910vfv15vg9xfqoluu.htm/, Retrieved Thu, 02 May 2024 10:10:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300719, Retrieved Thu, 02 May 2024 10:10:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90

Tree of Dependent Computations

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-     [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2015-11-15 16:35:00] [32b17a345b130fdf5cc88718ed94a974]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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Dataseries Y:
Download CSV
Histogram 
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Tables (Output of Computation)





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=300719&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=300719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300719&T=0

As an alternative you can also use a QR Code:  
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
Mean9.3203592814371317.2814371257485
Biased Variance2.252160349958773.16031410233425
Biased Standard Deviation1.500719943879861.77772722945177
Covariance0.189416348026838
Correlation0.0705739291758687
Determination0.00498067947932053
T-Test0.908804591592805
p-value (2 sided)0.364778805801143
p-value (1 sided)0.182389402900571
95% CI of Correlation[-0.0821703351416807, 0.220078804913897]
Degrees of Freedom165
Number of Observations167

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 9.32035928143713 & 17.2814371257485 \tabularnewline
Biased Variance & 2.25216034995877 & 3.16031410233425 \tabularnewline
Biased Standard Deviation & 1.50071994387986 & 1.77772722945177 \tabularnewline
Covariance & 0.189416348026838 \tabularnewline
Correlation & 0.0705739291758687 \tabularnewline
Determination & 0.00498067947932053 \tabularnewline
T-Test & 0.908804591592805 \tabularnewline
p-value (2 sided) & 0.364778805801143 \tabularnewline
p-value (1 sided) & 0.182389402900571 \tabularnewline
95% CI of Correlation & [-0.0821703351416807, 0.220078804913897] \tabularnewline
Degrees of Freedom & 165 \tabularnewline
Number of Observations & 167 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300719&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]9.32035928143713[/C][C]17.2814371257485[/C][/ROW]
[ROW][C]Biased Variance[/C][C]2.25216034995877[/C][C]3.16031410233425[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]1.50071994387986[/C][C]1.77772722945177[/C][/ROW]
[ROW][C]Covariance[/C][C]0.189416348026838[/C][/ROW]
[ROW][C]Correlation[/C][C]0.0705739291758687[/C][/ROW]
[ROW][C]Determination[/C][C]0.00498067947932053[/C][/ROW]
[ROW][C]T-Test[/C][C]0.908804591592805[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.364778805801143[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.182389402900571[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.0821703351416807, 0.220078804913897][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]165[/C][/ROW]
[ROW][C]Number of Observations[/C][C]167[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300719&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean9.3203592814371317.2814371257485
Biased Variance2.252160349958773.16031410233425
Biased Standard Deviation1.500719943879861.77772722945177
Covariance0.189416348026838
Correlation0.0705739291758687
Determination0.00498067947932053
T-Test0.908804591592805
p-value (2 sided)0.364778805801143
p-value (1 sided)0.182389402900571
95% CI of Correlation[-0.0821703351416807, 0.220078804913897]
Degrees of Freedom165
Number of Observations167






Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 65.382, p-value = 6.328e-15
alternative hypothesis: greater

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.8899, p-value = 0.08673
alternative hypothesis: greater

> ad.x
	Anderson-Darling normality test
data:  x
A = 5.2201, p-value = 6.056e-13

> ad.y
	Anderson-Darling normality test
data:  y
A = 2.887, p-value = 2.748e-07


\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline

> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 65.382, p-value = 6.328e-15
alternative hypothesis: greater

 \tabularnewline

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.8899, p-value = 0.08673
alternative hypothesis: greater

 \tabularnewline

> ad.x
	Anderson-Darling normality test
data:  x
A = 5.2201, p-value = 6.056e-13

 \tabularnewline

> ad.y
	Anderson-Darling normality test
data:  y
A = 2.887, p-value = 2.748e-07

 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300719&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 65.382, p-value = 6.328e-15
alternative hypothesis: greater

[/C][/ROW]
[ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.8899, p-value = 0.08673
alternative hypothesis: greater

[/C][/ROW]
[ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 5.2201, p-value = 6.056e-13

[/C][/ROW]
[ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 2.887, p-value = 2.748e-07

[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300719&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 65.382, p-value = 6.328e-15
alternative hypothesis: greater

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 4.8899, p-value = 0.08673
alternative hypothesis: greater

> ad.x
	Anderson-Darling normality test
data:  x
A = 5.2201, p-value = 6.056e-13

> ad.y
	Anderson-Darling normality test
data:  y
A = 2.887, p-value = 2.748e-07


Figures (Output of Computation)

Input Parameters & R Code

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()