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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationSun, 19 Oct 2008 12:36:23 -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/t12244414362d013i1bvfh04ma.htm/, Retrieved Wed, 29 May 2024 06:42:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17038, Retrieved Wed, 29 May 2024 06:42:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Pearson Correlation] [] [2008-10-19 18:36:23] [30d0d2777c6b98185041faaa081fb357] [Current]
Feedback Forum
2008-10-23 10:37:21 [Ellen Smolders] [reply] 
De student heeft het juiste geantwoord gegeven. Uit de berekeningen kunnen we afleiden dat er een eerder zwakke negatieve correlatie van -0.596 bestaat tussen de werkloosheid en goud. Dit kunnen we ook visueel vaststellen adhv de correlatiegrafieK.
2008-10-24 14:22:57 [Stijn Van de Velde] [reply] 
De student trekt ook hier weer de juiste conclusies.

De negatieve correlatie van 60% is ook duidelijk op de grafiek zichtbaar.
2008-10-26 14:07:27 [Natascha Meeus] [reply] 
De student geeft het juiste antwoord. Er is een negatieve correlatie van -0.59 en deze is ook zichbaar op de grafiek.
2008-10-27 16:23:09 [Bonifer Spillemaeckers] [reply] 
Uit de grafiek kunnen we goed afleiden dat het om een negatieve correlatie gaat.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10.846
10.413
10.709
10.662
10.570
10.297
10.635
10.872
10.296
10.383
10.431
10.574
10.653
10.805
10.872
10.625
10.407
10.463
10.556
10.646
10.702
11.353
11.346
11.451
11.964
12.574
13.031
13.812
14.544
14.931
14.886
16.005
17.064
15.168
16.050
15.839
15.137
14.954
15.648
15.305
15.579
16.348
15.928
16.171
15.937
15.713
15.594
15.683
16.438
17.032
17.696
17.745
19.394
20.148
20.108
18.584
18.441
18.391
19.178
18.079
18.483
Dataseries Y:
Download CSV
Histogram 
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17038&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17038&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17038&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean14.1008032786885562.393442622951
Biased Variance9.864468879333511572.27143241064
Biased Standard Deviation3.1407752035657639.6518780439293
Covariance-75.5374713114754
Correlation-0.596599990915803
Determination0.355931549160737
T-Test-5.71009370391526
p-value (2 sided)3.89417578230942e-07
p-value (1 sided)1.94708789115471e-07
Degrees of Freedom59
Number of Observations61

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 14.1008032786885 & 562.393442622951 \tabularnewline
Biased Variance & 9.86446887933351 & 1572.27143241064 \tabularnewline
Biased Standard Deviation & 3.14077520356576 & 39.6518780439293 \tabularnewline
Covariance & -75.5374713114754 \tabularnewline
Correlation & -0.596599990915803 \tabularnewline
Determination & 0.355931549160737 \tabularnewline
T-Test & -5.71009370391526 \tabularnewline
p-value (2 sided) & 3.89417578230942e-07 \tabularnewline
p-value (1 sided) & 1.94708789115471e-07 \tabularnewline
Degrees of Freedom & 59 \tabularnewline
Number of Observations & 61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17038&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]14.1008032786885[/C][C]562.393442622951[/C][/ROW]
[ROW][C]Biased Variance[/C][C]9.86446887933351[/C][C]1572.27143241064[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]3.14077520356576[/C][C]39.6518780439293[/C][/ROW]
[ROW][C]Covariance[/C][C]-75.5374713114754[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.596599990915803[/C][/ROW]
[ROW][C]Determination[/C][C]0.355931549160737[/C][/ROW]
[ROW][C]T-Test[/C][C]-5.71009370391526[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]3.89417578230942e-07[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]1.94708789115471e-07[/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=17038&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17038&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
Mean14.1008032786885562.393442622951
Biased Variance9.864468879333511572.27143241064
Biased Standard Deviation3.1407752035657639.6518780439293
Covariance-75.5374713114754
Correlation-0.596599990915803
Determination0.355931549160737
T-Test-5.71009370391526
p-value (2 sided)3.89417578230942e-07
p-value (1 sided)1.94708789115471e-07
Degrees of Freedom59
Number of Observations61


Figures (Output of Computation)

Input Parameters & R Code

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')