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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 computationMon, 05 Dec 2016 20:31:46 +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/05/t1480966462hov2udg4746vob6.htm/, Retrieved Wed, 01 May 2024 13:58:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297746, Retrieved Wed, 01 May 2024 13:58:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [H1: correlatie test ] [2016-12-05 19:31:46] [31f526a885cd288e1bc58dc4a6a7fb1f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2
4
4
4
3
4
1
4
3
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2
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1
NA
4
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5
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NA
4
2
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1
3
3
3
4
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2
5
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3
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2
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5
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1
4
3
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5
5
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5
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3
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1
5
4
3
4
4
4
4
2
4
4
4
4
3
4
5
2
5
4
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NA
2
2
2
4
4
5
3
3
4
4
4
4
4
4
4
2
5
4
4
4
4
4
2
3
3
4
4
4
4
3
3
Dataseries Y:
Download CSV
Histogram 
2
1
2
3
3
2
3
3
3
2
2
3
2
2
2
3
2
NA
3
2
2
3
2
3
2
2
2
2
3
2
3
2
2
2
2
2
3
2
2
3
2
3
2
3
2
NA
3
3
2
2
3
2
2
1
2
2
3
2
3
4
3
2
3
2
2
2
2
2
2
2
2
2
2
NA
1
2
2
2
2
3
3
2
2
2
3
2
3
3
2
2
3
4
3
3
3
2
3
2
5
3
4
2
2
2
2
2
3
2
2
3
3
3
2
1
2
2
2
2
3
2
2
3
3
2
3
3
4
2
2
3
2
2
3
2
2
NA
2
NA
2
1
3
2
3
2
2
2
2
2
2
2
2
2
3
2
2
3
3
2
4
2
2
2
4
3
3
2
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2
3

Tables (Output of Computation)





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=297746&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=297746&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297746&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 time3 seconds
R ServerBig Analytics Cloud Computing Center






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean3.56790123456792.38271604938272
Biased Variance0.9984758420972410.409083981100442
Biased Standard Deviation0.9992376304449520.639596733184623
Covariance-0.0509930220075148
Correlation-0.0792951443737874
Determination0.00628771992125979
T-Test-1.006181335837
p-value (2 sided)0.315847594983877
p-value (1 sided)0.157923797491939
95% CI of Correlation[-0.230670207676837, 0.0758274507793273]
Degrees of Freedom160
Number of Observations162

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 3.5679012345679 & 2.38271604938272 \tabularnewline
Biased Variance & 0.998475842097241 & 0.409083981100442 \tabularnewline
Biased Standard Deviation & 0.999237630444952 & 0.639596733184623 \tabularnewline
Covariance & -0.0509930220075148 \tabularnewline
Correlation & -0.0792951443737874 \tabularnewline
Determination & 0.00628771992125979 \tabularnewline
T-Test & -1.006181335837 \tabularnewline
p-value (2 sided) & 0.315847594983877 \tabularnewline
p-value (1 sided) & 0.157923797491939 \tabularnewline
95% CI of Correlation & [-0.230670207676837, 0.0758274507793273] \tabularnewline
Degrees of Freedom & 160 \tabularnewline
Number of Observations & 162 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297746&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]3.5679012345679[/C][C]2.38271604938272[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.998475842097241[/C][C]0.409083981100442[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.999237630444952[/C][C]0.639596733184623[/C][/ROW]
[ROW][C]Covariance[/C][C]-0.0509930220075148[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.0792951443737874[/C][/ROW]
[ROW][C]Determination[/C][C]0.00628771992125979[/C][/ROW]
[ROW][C]T-Test[/C][C]-1.006181335837[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.315847594983877[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.157923797491939[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.230670207676837, 0.0758274507793273][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]160[/C][/ROW]
[ROW][C]Number of Observations[/C][C]162[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297746&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297746&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
Mean3.56790123456792.38271604938272
Biased Variance0.9984758420972410.409083981100442
Biased Standard Deviation0.9992376304449520.639596733184623
Covariance-0.0509930220075148
Correlation-0.0792951443737874
Determination0.00628771992125979
T-Test-1.006181335837
p-value (2 sided)0.315847594983877
p-value (1 sided)0.157923797491939
95% CI of Correlation[-0.230670207676837, 0.0758274507793273]
Degrees of Freedom160
Number of Observations162






Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 17.487, p-value = 0.0001595
alternative hypothesis: greater

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.359, p-value = 1.55e-07
alternative hypothesis: greater

> ad.x
	Anderson-Darling normality test
data:  x
A = 11.258, p-value < 2.2e-16

> ad.y
	Anderson-Darling normality test
data:  y
A = 19.817, p-value < 2.2e-16


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

> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 17.487, p-value = 0.0001595
alternative hypothesis: greater

 \tabularnewline

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.359, p-value = 1.55e-07
alternative hypothesis: greater

 \tabularnewline

> ad.x
	Anderson-Darling normality test
data:  x
A = 11.258, p-value < 2.2e-16

 \tabularnewline

> ad.y
	Anderson-Darling normality test
data:  y
A = 19.817, p-value < 2.2e-16

 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297746&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 17.487, p-value = 0.0001595
alternative hypothesis: greater

[/C][/ROW]
[ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.359, p-value = 1.55e-07
alternative hypothesis: greater

[/C][/ROW]
[ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 11.258, p-value < 2.2e-16

[/C][/ROW]
[ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 19.817, p-value < 2.2e-16

[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297746&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297746&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 = 17.487, p-value = 0.0001595
alternative hypothesis: greater

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.359, p-value = 1.55e-07
alternative hypothesis: greater

> ad.x
	Anderson-Darling normality test
data:  x
A = 11.258, p-value < 2.2e-16

> ad.y
	Anderson-Darling normality test
data:  y
A = 19.817, p-value < 2.2e-16


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()