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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 computationTue, 24 Aug 2021 21:46:12 +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/2021/Aug/24/t162983461874wm7csods2ferg.htm/, Retrieved Tue, 07 May 2024 22:01:14 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Tue, 07 May 2024 22:01:14 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
17.65
14.73
14.42
14.25
13.25
13
12.88
12.55
12.55
12.25
12.17
11.92
11.83
11.83
11.83
11.75
11.5
11.13
10.98
10.92
10.75
10.75
10.42
10.37
10.33
10.08
9.92
9.92
9.83
9.75
9.67
9.5
9.5
9.42
9.42
9.33
9.33
9.33
9.17
9.08
8.92
8.75
8.67
8.67
8.42
8.42
7.83
7.25
7.2
7.08
7
6.68
6.25
6.08
4.95
4.83
4.67
4.67
4.67
4.58
4.5
4.42
4.25
4.2
4
4
3.92
3.83
3.83
3.75
3.67
3.58
3.5
3.25
3.08
3.01
2.92
2.67
2.58
1.92
1.92
1.92
1.75
1.58
1.5
Dataseries Y:
Download CSV
Histogram 
0.048039393
0.028617266
0.043897401
0.037921916
0.034858029
0.035367977
-0.034314403
-0.050206147
-0.006673568
-0.005645236
0.036705802
-0.04883016
-0.04246415
0.028102235
0.045416898
0.045337598
0.058104415
0.068221824
0.05518858
-0.094313291
0.017882448
0.032225766
0.020961312
-0.023457836
0.031692308
0.055622072
-0.026501631
0.036046831
0.019520915
0.019327536
0.048803311
0.010517316
0.08251273
0.010704201
0.079762372
-0.04076562
0.029558254
0.047059981
0.037188219
0.009760321
-0.05392437
0.036000653
0.024662875
0.048006106
0.035195548
0.07455616
0.008798738
0.075130045
0.062616504
0.005909709
0.043406273
0.058298483
0.038064971
0.054854416
0.071416681
0.050199253
-0.025985931
0.09467892
0.095599331
0.026845791
0.082272755
0.053489607
0.052316204
0.048852251
0.101723967
0.117299836
0.059891183
-0.065838416
0.043376261
0.098226083
0.081887782
0.079125092
0.09420638
0.062800417
0.138426495
0.098552722
0.066037087
0.097924199
0.190815015
0.105659879
0.112856232
0.209806635
0.206546712
0.116861337
0.165651732

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/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:  
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 time2 seconds
R ServerBig Analytics Cloud Computing Center






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean7.816470588235290.0473511857411765
Biased Variance14.49503695501730.00304982585261907
Biased Standard Deviation3.807234817425540.0552252284071245
Covariance-0.12650634278021
Correlation-0.594600783128166
Determination0.353550091296629
T-Test-6.73747371413984
p-value (2 sided)1.97318578262705e-09
p-value (1 sided)9.86592891313524e-10
95% CI of Correlation[-0.716879242574732, -0.43683393280442]
Degrees of Freedom83
Number of Observations85

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 7.81647058823529 & 0.0473511857411765 \tabularnewline
Biased Variance & 14.4950369550173 & 0.00304982585261907 \tabularnewline
Biased Standard Deviation & 3.80723481742554 & 0.0552252284071245 \tabularnewline
Covariance & -0.12650634278021 \tabularnewline
Correlation & -0.594600783128166 \tabularnewline
Determination & 0.353550091296629 \tabularnewline
T-Test & -6.73747371413984 \tabularnewline
p-value (2 sided) & 1.97318578262705e-09 \tabularnewline
p-value (1 sided) & 9.86592891313524e-10 \tabularnewline
95% CI of Correlation & [-0.716879242574732, -0.43683393280442] \tabularnewline
Degrees of Freedom & 83 \tabularnewline
Number of Observations & 85 \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]7.81647058823529[/C][C]0.0473511857411765[/C][/ROW]
[ROW][C]Biased Variance[/C][C]14.4950369550173[/C][C]0.00304982585261907[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]3.80723481742554[/C][C]0.0552252284071245[/C][/ROW]
[ROW][C]Covariance[/C][C]-0.12650634278021[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.594600783128166[/C][/ROW]
[ROW][C]Determination[/C][C]0.353550091296629[/C][/ROW]
[ROW][C]T-Test[/C][C]-6.73747371413984[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]1.97318578262705e-09[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]9.86592891313524e-10[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][-0.716879242574732, -0.43683393280442][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]83[/C][/ROW]
[ROW][C]Number of Observations[/C][C]85[/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:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean7.816470588235290.0473511857411765
Biased Variance14.49503695501730.00304982585261907
Biased Standard Deviation3.807234817425540.0552252284071245
Covariance-0.12650634278021
Correlation-0.594600783128166
Determination0.353550091296629
T-Test-6.73747371413984
p-value (2 sided)1.97318578262705e-09
p-value (1 sided)9.86592891313524e-10
95% CI of Correlation[-0.716879242574732, -0.43683393280442]
Degrees of Freedom83
Number of Observations85






Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 3.2543, p-value = 0.1965
alternative hypothesis: greater

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 6.506, p-value = 0.03866
alternative hypothesis: greater

> ad.x
	Anderson-Darling normality test
data:  x
A = 1.5226, p-value = 0.0005906

> ad.y
	Anderson-Darling normality test
data:  y
A = 1.121, p-value = 0.005852


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

> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 3.2543, p-value = 0.1965
alternative hypothesis: greater

 \tabularnewline

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 6.506, p-value = 0.03866
alternative hypothesis: greater

 \tabularnewline

> ad.x
	Anderson-Darling normality test
data:  x
A = 1.5226, p-value = 0.0005906

 \tabularnewline

> ad.y
	Anderson-Darling normality test
data:  y
A = 1.121, p-value = 0.005852

 \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 = 3.2543, p-value = 0.1965
alternative hypothesis: greater

[/C][/ROW]
[ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 6.506, p-value = 0.03866
alternative hypothesis: greater

[/C][/ROW]
[ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 1.5226, p-value = 0.0005906

[/C][/ROW]
[ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 1.121, p-value = 0.005852

[/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:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 3.2543, p-value = 0.1965
alternative hypothesis: greater

> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 6.506, p-value = 0.03866
alternative hypothesis: greater

> ad.x
	Anderson-Darling normality test
data:  x
A = 1.5226, p-value = 0.0005906

> ad.y
	Anderson-Darling normality test
data:  y
A = 1.121, p-value = 0.005852


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()