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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 computationThu, 07 Dec 2017 12:01:32 +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/2017/Dec/07/t15126446367ev14duz7s19uf7.htm/, Retrieved Wed, 15 May 2024 10:21:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308691, Retrieved Wed, 15 May 2024 10:21:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [Pearson] [2017-12-07 11:01:32] [6ed64e8c4e855e992fbbfd41bce49003] [Current]
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Dataseries X:
64
56
56
63
67
64
64
64
69
60
59
56
63
67
69
58
58
61
62
59
55
65
57
69
59
63
56
63
67
55
55
68
68
68
63
60
64
57
55
59
59
55
64
66
57
69
59
61
60
60
73
61
64
61
62
56
59
68
59
65
Dataseries Y:
1
6
25
20
35
13
2
10
26
5
1
8
7
40
18
2
2
20
24
5
12
15
10
9
9
10
20
10
10
6
17
20
6
20
7
2
26
2
5
10
3
2
35
10
2
5
12
15
6
3
25
9
6
3
3
1
12
20
14
6




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 time6 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308691&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]6 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308691&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308691&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 time6 seconds
R ServerBig Analytics Cloud Computing Center







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean61.716666666666711.4666666666667
Biased Variance20.369722222222284.7822222222222
Biased Standard Deviation4.513282865301299.20772622433043
Covariance17.3378531073446
Correlation0.410252398918009
Determination0.168307030817981
T-Test3.42597043595097
p-value (2 sided)0.00113173258337826
p-value (1 sided)0.000565866291689129
95% CI of Correlation[0.174506611887196, 0.601515315090988]
Degrees of Freedom58
Number of Observations60

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 61.7166666666667 & 11.4666666666667 \tabularnewline
Biased Variance & 20.3697222222222 & 84.7822222222222 \tabularnewline
Biased Standard Deviation & 4.51328286530129 & 9.20772622433043 \tabularnewline
Covariance & 17.3378531073446 \tabularnewline
Correlation & 0.410252398918009 \tabularnewline
Determination & 0.168307030817981 \tabularnewline
T-Test & 3.42597043595097 \tabularnewline
p-value (2 sided) & 0.00113173258337826 \tabularnewline
p-value (1 sided) & 0.000565866291689129 \tabularnewline
95% CI of Correlation & [0.174506611887196, 0.601515315090988] \tabularnewline
Degrees of Freedom & 58 \tabularnewline
Number of Observations & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308691&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]61.7166666666667[/C][C]11.4666666666667[/C][/ROW]
[ROW][C]Biased Variance[/C][C]20.3697222222222[/C][C]84.7822222222222[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]4.51328286530129[/C][C]9.20772622433043[/C][/ROW]
[ROW][C]Covariance[/C][C]17.3378531073446[/C][/ROW]
[ROW][C]Correlation[/C][C]0.410252398918009[/C][/ROW]
[ROW][C]Determination[/C][C]0.168307030817981[/C][/ROW]
[ROW][C]T-Test[/C][C]3.42597043595097[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.00113173258337826[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.000565866291689129[/C][/ROW]
[ROW][C]95% CI of Correlation[/C][C][0.174506611887196, 0.601515315090988][/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]58[/C][/ROW]
[ROW][C]Number of Observations[/C][C]60[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308691&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308691&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
Mean61.716666666666711.4666666666667
Biased Variance20.369722222222284.7822222222222
Biased Standard Deviation4.513282865301299.20772622433043
Covariance17.3378531073446
Correlation0.410252398918009
Determination0.168307030817981
T-Test3.42597043595097
p-value (2 sided)0.00113173258337826
p-value (1 sided)0.000565866291689129
95% CI of Correlation[0.174506611887196, 0.601515315090988]
Degrees of Freedom58
Number of Observations60







Normality Tests
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 2.4703, p-value = 0.2908
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 13.975, p-value = 0.0009232
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.73504, p-value = 0.05248
> ad.y
	Anderson-Darling normality test
data:  y
A = 2.0482, p-value = 2.829e-05

\begin{tabular}{lllllllll}
\hline
Normality Tests \tabularnewline
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 2.4703, p-value = 0.2908
alternative hypothesis: greater
\tabularnewline
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 13.975, p-value = 0.0009232
alternative hypothesis: greater
\tabularnewline
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.73504, p-value = 0.05248
\tabularnewline
> ad.y
	Anderson-Darling normality test
data:  y
A = 2.0482, p-value = 2.829e-05
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=308691&T=2

[TABLE]
[ROW][C]Normality Tests[/C][/ROW]
[ROW][C]
> jarque.x
	Jarque-Bera Normality Test
data:  x
JB = 2.4703, p-value = 0.2908
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 13.975, p-value = 0.0009232
alternative hypothesis: greater
[/C][/ROW] [ROW][C]
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.73504, p-value = 0.05248
[/C][/ROW] [ROW][C]
> ad.y
	Anderson-Darling normality test
data:  y
A = 2.0482, p-value = 2.829e-05
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308691&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308691&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 = 2.4703, p-value = 0.2908
alternative hypothesis: greater
> jarque.y
	Jarque-Bera Normality Test
data:  y
JB = 13.975, p-value = 0.0009232
alternative hypothesis: greater
> ad.x
	Anderson-Darling normality test
data:  x
A = 0.73504, p-value = 0.05248
> ad.y
	Anderson-Darling normality test
data:  y
A = 2.0482, p-value = 2.829e-05



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()