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Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationWed, 05 Aug 2020 18:41:21 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Aug/05/t1596646087motj3ix6cnk6spy.htm/, Retrieved Thu, 18 Apr 2024 03:40:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319209, Retrieved Thu, 18 Apr 2024 03:40:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [correlazione digi...] [2020-08-05 16:41:21] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0,316802719
0,14521453
0,117491674
0,082490838
0,021091041
0,013318853
0,011609144
0,000748045
0,00622416
0,004089691
0,000694873
0
0,521201192
0,201699388
0,117006996
0,048324347
0,022072839
Dataseries Y:
0,280463211
0,127942483
0,105134463
0,077613225
0,013858178
0,007856648
0,006444501
0,002176303
0,001333778
0,001651696
0,000817826
0,000680965
0,135058721
0,120203957
0,04849238
0,020453535
0,014090431




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319209&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319209&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319209&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean0.09588707823529410.0567219000588235
Biased Variance0.01855391375994070.00549261963369122
Biased Standard Deviation0.136212751825740.0741122097477279
Covariance0.00848902230729525
Correlation0.791445851097491
Determination0.626386535219432
T-Test5.01482262479981
p-value (2 sided)0.000153887611020665
p-value (1 sided)7.69438055103324e-05
95% CI of Correlation[0.50161918167496, 0.92153480808692]
Degrees of Freedom15
Number of Observations17

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 0.0958870782352941 & 0.0567219000588235 \tabularnewline
Biased Variance & 0.0185539137599407 & 0.00549261963369122 \tabularnewline
Biased Standard Deviation & 0.13621275182574 & 0.0741122097477279 \tabularnewline
Covariance & 0.00848902230729525 \tabularnewline
Correlation & 0.791445851097491 \tabularnewline
Determination & 0.626386535219432 \tabularnewline
T-Test & 5.01482262479981 \tabularnewline
p-value (2 sided) & 0.000153887611020665 \tabularnewline
p-value (1 sided) & 7.69438055103324e-05 \tabularnewline
95% CI of Correlation & [0.50161918167496, 0.92153480808692] \tabularnewline
Degrees of Freedom & 15 \tabularnewline
Number of Observations & 17 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319209&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]0.0958870782352941[/C][C]0.0567219000588235[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.0185539137599407[/C][C]0.00549261963369122[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.13621275182574[/C][C]0.0741122097477279[/C][/ROW]
[ROW][C]Covariance[/C][C]0.00848902230729525[/C][/ROW]
[ROW][C]Correlation[/C][C]0.791445851097491[/C][/ROW]
[ROW][C]Determination[/C][C]0.626386535219432[/C][/ROW]
[ROW][C]T-Test[/C][C]5.01482262479981[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.000153887611020665[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]7.69438055103324e-05[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][0.50161918167496, 0.92153480808692][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]15[/C][/ROW]
[ROW][C]Number of Observations[/C][C]17[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319209&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319209&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
Mean0.09588707823529410.0567219000588235
Biased Variance0.01855391375994070.00549261963369122
Biased Standard Deviation0.136212751825740.0741122097477279
Covariance0.00848902230729525
Correlation0.791445851097491
Determination0.626386535219432
T-Test5.01482262479981
p-value (2 sided)0.000153887611020665
p-value (1 sided)7.69438055103324e-05
95% CI of Correlation[0.50161918167496, 0.92153480808692]
Degrees of Freedom15
Number of Observations17







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 17.406, p-value = 0.000166
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 10.699, p-value = 0.004749
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.7318, p-value = 0.000118
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.5048, p-value = 0.0004543

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 17.406, p-value = 0.000166
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 10.699, p-value = 0.004749
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.7318, p-value = 0.000118
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.5048, p-value = 0.0004543
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=319209&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 17.406, p-value = 0.000166
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 10.699, p-value = 0.004749
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.7318, p-value = 0.000118
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.5048, p-value = 0.0004543
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319209&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319209&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 = 17.406, p-value = 0.000166
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 10.699, p-value = 0.004749
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.7318, p-value = 0.000118
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.5048, p-value = 0.0004543



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()