Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationSun, 19 Oct 2008 12:31:50 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/19/t1224441147f8f350sda4w6dmy.htm/, Retrieved Sun, 19 May 2024 14:55:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17033, Retrieved Sun, 19 May 2024 14:55:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Pearson Correlation] [Correlatie rente ...] [2008-10-19 18:31:50] [7f3f68cb5622d7511b280fd3e248ef1b] [Current]
Feedback Forum
2008-10-23 10:35:07 [Ellen Smolders] [reply
De student heeft het juiste antwoord gegeven. We kunnen uit de berekeningen afleiden dat er een sterke negatieve correlatie bestaat van -0.709 tussen de werkloosheid en de rente. Ook kunnen we dit visueel vaststellen op de correlatiegrafiek.
2008-10-24 14:21:07 [Stijn Van de Velde] [reply
De student trekt hier de juiste conclusies. Zowel het correlatie getal als de grafiek laten zien dat er een negatief verband is tussen rente en werkloosheid.
2008-10-26 13:56:30 [Natascha Meeus] [reply
Er is inderdaad een sterke negatieve correlatie tussen de rente en de werkloosheid.
2008-10-27 16:22:12 [Bonifer Spillemaeckers] [reply
We kunnen inderdaad op de grafiek zien dat het om een negatieve correlatie gaat.

Post a new message
Dataseries X:
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,00
2,21
2,25
2,25
2,45
2,50
2,50
2,64
2,75
2,93
3,00
3,17
3,25
3,39
3,50
3,50
3,65
3,75
3,75
3,90
4,00
4,00
4,00
4,00
4,00
4,00
4,00
4,00
4,00
4,00
4,00
4,00
4,18
4,25
4,25
Dataseries Y:
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17033&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17033&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17033&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean2.82562.393442622951
Biased Variance0.7768950819672131572.27143241064
Biased Standard Deviation0.88141652013518239.6518780439293
Covariance-25.2003333333333
Correlation-0.709222904661576
Determination0.502997128496603
T-Test-7.7273273364816
p-value (2 sided)1.58379664630574e-10
p-value (1 sided)7.91898323152868e-11
Degrees of Freedom59
Number of Observations61

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 2.82 & 562.393442622951 \tabularnewline
Biased Variance & 0.776895081967213 & 1572.27143241064 \tabularnewline
Biased Standard Deviation & 0.881416520135182 & 39.6518780439293 \tabularnewline
Covariance & -25.2003333333333 \tabularnewline
Correlation & -0.709222904661576 \tabularnewline
Determination & 0.502997128496603 \tabularnewline
T-Test & -7.7273273364816 \tabularnewline
p-value (2 sided) & 1.58379664630574e-10 \tabularnewline
p-value (1 sided) & 7.91898323152868e-11 \tabularnewline
Degrees of Freedom & 59 \tabularnewline
Number of Observations & 61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17033&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]2.82[/C][C]562.393442622951[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.776895081967213[/C][C]1572.27143241064[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.881416520135182[/C][C]39.6518780439293[/C][/ROW]
[ROW][C]Covariance[/C][C]-25.2003333333333[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.709222904661576[/C][/ROW]
[ROW][C]Determination[/C][C]0.502997128496603[/C][/ROW]
[ROW][C]T-Test[/C][C]-7.7273273364816[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]1.58379664630574e-10[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]7.91898323152868e-11[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]59[/C][/ROW]
[ROW][C]Number of Observations[/C][C]61[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17033&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17033&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
Mean2.82562.393442622951
Biased Variance0.7768950819672131572.27143241064
Biased Standard Deviation0.88141652013518239.6518780439293
Covariance-25.2003333333333
Correlation-0.709222904661576
Determination0.502997128496603
T-Test-7.7273273364816
p-value (2 sided)1.58379664630574e-10
p-value (1 sided)7.91898323152868e-11
Degrees of Freedom59
Number of Observations61



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
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)
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')
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,'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')