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 09:45:56 +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/t1472373996kaqwdpaqn12c4ob.htm/, Retrieved Sat, 04 May 2024 19:36:21 +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 19:36:21 +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:
9.2
11.7
15.8
8.6
23.2
27.4
9.3
16
4.7
12.5
20.1
9.1
8.1
8.6
20.3
25
19.2
3.3
11.2
10.5
10.1
7.2
13.6
9
24.6
12.6
5.6
8.7
7.7
24.1
11.7
7.7
9.6
7.2
12.3
8.9
13.6
11.2
2.8
3.2
9.4
11.9
15.4
7.4
18.9
7.9
12.2
11
2.8
11.8
17.1
11.6
5.8
8.3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean6.5870370370370411.7907407407407
Biased Variance0.20668381344307334.1567661179698
Biased Standard Deviation0.4546249151147275.84437901902074
Covariance-0.186537386443046
Correlation-0.0689058971258809
Determination0.00474802265872248
T-Test-0.49807132439483
p-value (2 sided)0.620533814632749
p-value (1 sided)0.310266907316374
95% CI of Correlation[-0.330567389591635, 0.202592546061816]
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 & 11.7907407407407 \tabularnewline
Biased Variance & 0.206683813443073 & 34.1567661179698 \tabularnewline
Biased Standard Deviation & 0.454624915114727 & 5.84437901902074 \tabularnewline
Covariance & -0.186537386443046 \tabularnewline
Correlation & -0.0689058971258809 \tabularnewline
Determination & 0.00474802265872248 \tabularnewline
T-Test & -0.49807132439483 \tabularnewline
p-value (2 sided) & 0.620533814632749 \tabularnewline
p-value (1 sided) & 0.310266907316374 \tabularnewline
95% CI of Correlation & [-0.330567389591635, 0.202592546061816] \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]11.7907407407407[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.206683813443073[/C][C]34.1567661179698[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.454624915114727[/C][C]5.84437901902074[/C][/ROW]
[ROW][C]Covariance[/C][C]-0.186537386443046[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.0689058971258809[/C][/ROW]
[ROW][C]Determination[/C][C]0.00474802265872248[/C][/ROW]
[ROW][C]T-Test[/C][C]-0.49807132439483[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.620533814632749[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.310266907316374[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.330567389591635, 0.202592546061816][/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
Mean6.5870370370370411.7907407407407
Biased Variance0.20668381344307334.1567661179698
Biased Standard Deviation0.4546249151147275.84437901902074
Covariance-0.186537386443046
Correlation-0.0689058971258809
Determination0.00474802265872248
T-Test-0.49807132439483
p-value (2 sided)0.620533814632749
p-value (1 sided)0.310266907316374
95% CI of Correlation[-0.330567389591635, 0.202592546061816]
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 = 7.2448, p-value = 0.02672
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 = 1.5613, p-value = 0.0004512

\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 = 7.2448, p-value = 0.02672
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 = 1.5613, p-value = 0.0004512
\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 = 7.2448, p-value = 0.02672
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 = 1.5613, p-value = 0.0004512
[/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 = 7.2448, p-value = 0.02672
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 = 1.5613, p-value = 0.0004512



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()