Free Statistics

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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 computationSun, 28 Aug 2016 09:43:56 +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/Aug/28/t14723738573q7xrzivhhuvzfe.htm/, Retrieved Sat, 04 May 2024 10:22:39 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 04 May 2024 10:22:39 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
6.8
6.3
6.4
6.2
6.9
6.4
6.3
6.8
6.9
6.7
6.9
6.9
6.3
6.1
6.2
6.8
6.5
7.6
6.3
7.1
6.8
7.3
6.4
6.8
7.2
6.4
6.6
6.8
6.1
6.5
6.4
6
6
7.3
6.1
6.7
6.4
5.8
6.9
7
7.3
5.9
6.2
6.8
7
5.9
6.1
5.7
7.1
5.8
7.4
6.8
6.8
7
Dataseries Y:
0.672
0.797
0.761
0.651
0.9
0.78
0.771
0.75
0.818
0.825
0.632
0.757
0.709
0.782
0.775
0.88
0.833
0.571
0.816
0.714
0.765
0.655
0.244
0.728
0.721
0.757
0.747
0.739
0.713
0.742
0.861
0.721
0.785
0.655
0.821
0.728
0.846
0.813
0.595
0.573
0.726
0.707
0.804
0.784
0.744
0.839
0.79
0.701
0.778
0.872
0.713
0.701
0.734
0.764




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=&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=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
Mean6.587037037037040.741851851851852
Biased Variance0.2066838134430730.00984349657064472
Biased Standard Deviation0.4546249151147270.099214396992799
Covariance-0.0119151642208246
Correlation-0.259271160761967
Determination0.0672215348028579
T-Test-1.93582738068148
p-value (2 sided)0.0583339754485304
p-value (1 sided)0.0291669877242652
95% CI of Correlation[-0.492818947017149, 0.00912271552333516]
Degrees of Freedom52
Number of Observations54

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 6.58703703703704 & 0.741851851851852 \tabularnewline
Biased Variance & 0.206683813443073 & 0.00984349657064472 \tabularnewline
Biased Standard Deviation & 0.454624915114727 & 0.099214396992799 \tabularnewline
Covariance & -0.0119151642208246 \tabularnewline
Correlation & -0.259271160761967 \tabularnewline
Determination & 0.0672215348028579 \tabularnewline
T-Test & -1.93582738068148 \tabularnewline
p-value (2 sided) & 0.0583339754485304 \tabularnewline
p-value (1 sided) & 0.0291669877242652 \tabularnewline
95% CI of Correlation & [-0.492818947017149, 0.00912271552333516] \tabularnewline
Degrees of Freedom & 52 \tabularnewline
Number of Observations & 54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]6.58703703703704[/C][C]0.741851851851852[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.206683813443073[/C][C]0.00984349657064472[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.454624915114727[/C][C]0.099214396992799[/C][/ROW]
[ROW][C]Covariance[/C][C]-0.0119151642208246[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.259271160761967[/C][/ROW]
[ROW][C]Determination[/C][C]0.0672215348028579[/C][/ROW]
[ROW][C]T-Test[/C][C]-1.93582738068148[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.0583339754485304[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0291669877242652[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.492818947017149, 0.00912271552333516][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]52[/C][/ROW]
[ROW][C]Number of Observations[/C][C]54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
Mean6.587037037037040.741851851851852
Biased Variance0.2066838134430730.00984349657064472
Biased Standard Deviation0.4546249151147270.099214396992799
Covariance-0.0119151642208246
Correlation-0.259271160761967
Determination0.0672215348028579
T-Test-1.93582738068148
p-value (2 sided)0.0583339754485304
p-value (1 sided)0.0291669877242652
95% CI of Correlation[-0.492818947017149, 0.00912271552333516]
Degrees of Freedom52
Number of Observations54







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 1.4138, p-value = 0.4932
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 256.81, p-value < 2.2e-16
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.5451, p-value = 0.154
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.693, p-value = 0.0002121

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 1.4138, p-value = 0.4932
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 256.81, p-value < 2.2e-16
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.5451, p-value = 0.154
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.693, p-value = 0.0002121
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 1.4138, p-value = 0.4932
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 256.81, p-value < 2.2e-16
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.5451, p-value = 0.154
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.693, p-value = 0.0002121
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 = 1.4138, p-value = 0.4932
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 256.81, p-value < 2.2e-16
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.5451, p-value = 0.154
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.693, p-value = 0.0002121



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()