Free Statistics

of Irreproducible Research!

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, 10 Dec 2016 19:01:37 +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/10/t1481394348d6gc3qmzfldz168.htm/, Retrieved Fri, 01 Nov 2024 03:43:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298741, Retrieved Fri, 01 Nov 2024 03:43:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [pearson correlation] [2016-12-10 18:01:37] [34b674d558c9d5fa20516c65c4cfbe6a] [Current]
Feedback Forum

Post a new message
Dataseries X:
13
16
17
NA
NA
16
NA
NA
NA
17
17
15
16
14
16
17
NA
NA
NA
16
NA
16
NA
NA
NA
16
15
16
16
13
15
17
NA
13
17
NA
14
14
18
NA
17
13
16
15
15
NA
15
13
17
NA
NA
11
14
13
NA
17
16
NA
17
16
16
16
15
12
17
14
14
16
NA
NA
NA
NA
NA
15
16
14
15
17
NA
10
NA
17
NA
20
17
18
NA
17
14
NA
17
NA
17
NA
16
18
18
16
NA
NA
15
13
NA
NA
NA
NA
NA
16
NA
NA
NA
12
NA
16
16
NA
16
14
15
14
NA
15
NA
15
16
NA
NA
NA
11
NA
18
NA
11
NA
18
NA
15
19
17
NA
14
NA
13
17
14
19
14
NA
NA
16
16
15
12
NA
17
NA
NA
18
15
18
15
NA
NA
NA
16
NA
16
Dataseries Y:
14
19
17
17
15
20
15
19
15
15
19
NA
20
18
15
14
20
NA
16
16
10
19
19
16
15
18
17
19
17
10
NA
20
5
19
16
15
16
18
16
15
17
10
NA
19
7
13
16
16
18
NA
16
17
19
16
19
13
16
13
12
17
17
17
16
16
14
16
13
16
14
20
12
13
18
14
19
18
14
18
19
15
14
17
19
13
19
18
20
15
15
15
20
15
19
18
18
15
20
17
12
18
19
20
10
17
NA
16
18
18
14
15
12
17
14
18
17
17
20
16
14
15
18
20
17
17
17
17
15
17
18
17
20
15
16
15
18
11
15
18
20
19
14
16
15
17
18
20
17
18
15
16
11
15
18
17
16
12
19
18
15
17
19
18
19
16
16
16
14




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=298741&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=298741&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298741&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 time4 seconds
R ServerBig Analytics Cloud Computing Center







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean15.4816.63
Biased Variance3.56965.8931
Biased Standard Deviation1.889338508579132.42757080226304
Covariance0.795555555555556
Correlation0.171721243868946
Determination0.0294881855958979
T-Test1.72558616530011
p-value (2 sided)0.0875737521408717
p-value (1 sided)0.0437868760704359
95% CI of Correlation[-0.0255589560192374, 0.356127479570446]
Degrees of Freedom98
Number of Observations100

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 15.48 & 16.63 \tabularnewline
Biased Variance & 3.5696 & 5.8931 \tabularnewline
Biased Standard Deviation & 1.88933850857913 & 2.42757080226304 \tabularnewline
Covariance & 0.795555555555556 \tabularnewline
Correlation & 0.171721243868946 \tabularnewline
Determination & 0.0294881855958979 \tabularnewline
T-Test & 1.72558616530011 \tabularnewline
p-value (2 sided) & 0.0875737521408717 \tabularnewline
p-value (1 sided) & 0.0437868760704359 \tabularnewline
95% CI of Correlation & [-0.0255589560192374, 0.356127479570446] \tabularnewline
Degrees of Freedom & 98 \tabularnewline
Number of Observations & 100 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298741&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]15.48[/C][C]16.63[/C][/ROW]
[ROW][C]Biased Variance[/C][C]3.5696[/C][C]5.8931[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]1.88933850857913[/C][C]2.42757080226304[/C][/ROW]
[ROW][C]Covariance[/C][C]0.795555555555556[/C][/ROW]
[ROW][C]Correlation[/C][C]0.171721243868946[/C][/ROW]
[ROW][C]Determination[/C][C]0.0294881855958979[/C][/ROW]
[ROW][C]T-Test[/C][C]1.72558616530011[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.0875737521408717[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0437868760704359[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.0255589560192374, 0.356127479570446][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]98[/C][/ROW]
[ROW][C]Number of Observations[/C][C]100[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298741&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298741&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
Mean15.4816.63
Biased Variance3.56965.8931
Biased Standard Deviation1.889338508579132.42757080226304
Covariance0.795555555555556
Correlation0.171721243868946
Determination0.0294881855958979
T-Test1.72558616530011
p-value (2 sided)0.0875737521408717
p-value (1 sided)0.0437868760704359
95% CI of Correlation[-0.0255589560192374, 0.356127479570446]
Degrees of Freedom98
Number of Observations100







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 4.5228, p-value = 0.1042
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.563, p-value = 1.4e-07
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.9294, p-value = 5.91e-05
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.6357, p-value = 0.000314

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 4.5228, p-value = 0.1042
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.563, p-value = 1.4e-07
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.9294, p-value = 5.91e-05
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.6357, p-value = 0.000314
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=298741&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 4.5228, p-value = 0.1042
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.563, p-value = 1.4e-07
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.9294, p-value = 5.91e-05
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.6357, p-value = 0.000314
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298741&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298741&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 = 4.5228, p-value = 0.1042
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 31.563, p-value = 1.4e-07
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.9294, p-value = 5.91e-05
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.6357, p-value = 0.000314



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()