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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 computationMon, 20 Oct 2008 09:37:40 -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/20/t1224517144f8qddfndlqr2gzc.htm/, Retrieved Sun, 19 May 2024 14:54:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17500, Retrieved Sun, 19 May 2024 14:54:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Aandelenmarkt BEL20] [2008-10-13 21:32:58] [1932d3c8dcd9b7464ac83a0122118fa4]
-   PD  [Univariate Data Series] [Wisselkoers dolla...] [2008-10-20 14:32:36] [38f43994ada0e6172896e12525dcc585]
F RMPD      [Pearson Correlation] [correlatie wissel...] [2008-10-20 15:37:40] [284c7cdb9fcda2adcbb08e211682c8d6] [Current]
F    D        [Pearson Correlation] [correlatie wissel...] [2008-10-20 15:41:54] [38f43994ada0e6172896e12525dcc585]
F    D        [Pearson Correlation] [correlatie wissel...] [2008-10-20 15:45:17] [38f43994ada0e6172896e12525dcc585]
Feedback Forum
2008-10-27 20:38:57 [Olivier Uyttendaele] [reply] 
Berekening lijkt mij correct uitgevoerd.

Een correlatie van 0,76 is een redelijk sterk positief verband tussen de 2 reeksen.
Een zekere samenhang lijkt mij iets te zwak uitgedrukt.

Wanneer de vele observaties linksonderaan, beter verdeeld zou zijn, rond de diagonaal die we kunnen trekken door de overige observaties zou de correlatie nog beter zijn.

je kan ook eventueel de P value (2 sided) vermelden, deze geeft direct in % weer hoeveel kans er is dat de correlatie toeval is.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,1692
1,1702
1,2286
1,2613
1,2646
1,2262
1,1985
1,2007
1,2138
1,2266
1,2176
1,2218
1,249
1,2991
1,3408
1,3119
1,3014
1,3201
1,2938
1,2694
1,2165
1,2037
1,2292
1,2256
1,2015
1,1786
1,1856
1,2103
1,1938
1,202
1,2271
1,277
1,265
1,2684
1,2811
1,2727
1,2611
1,2881
1,3213
1,2999
1,3074
1,3242
1,3516
1,3511
1,3419
1,3716
1,3622
1,3896
1,4227
1,4684
1,457
1,4718
1,4748
1,5527
1,575
1,5557
1,5553
1,577
1,4975
1,4369
Dataseries Y:
Download CSV
Histogram 
10413
10709
10662
10570
10297
10635
10872
10296
10383
10431
10574
10653
10805
10872
10625
10407
10463
10556
10646
10702
11353
11346
11451
11964
12574
13031
13812
14544
14931
14886
16005
17064
15168
16050
15839
15137
14954
15648
15305
15579
16348
15928
16171
15937
15713
15594
15683
16438
17032
17696
17745
19394
20148
20108
18584
18441
18391
19178
18079
18483

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=17500&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=17500&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17500&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
Mean1.31062514155.05
Biased Variance0.01256712154166679849371.58083333
Biased Standard Deviation0.112103173646723138.37084820028
Covariance272.924598728814
Correlation0.762818598196512
Determination0.581892213754492
T-Test8.98444267686047
p-value (2 sided)1.40687461680500e-12
p-value (1 sided)7.03437308402499e-13
Degrees of Freedom58
Number of Observations60

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 1.310625 & 14155.05 \tabularnewline
Biased Variance & 0.0125671215416667 & 9849371.58083333 \tabularnewline
Biased Standard Deviation & 0.11210317364672 & 3138.37084820028 \tabularnewline
Covariance & 272.924598728814 \tabularnewline
Correlation & 0.762818598196512 \tabularnewline
Determination & 0.581892213754492 \tabularnewline
T-Test & 8.98444267686047 \tabularnewline
p-value (2 sided) & 1.40687461680500e-12 \tabularnewline
p-value (1 sided) & 7.03437308402499e-13 \tabularnewline
Degrees of Freedom & 58 \tabularnewline
Number of Observations & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17500&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]1.310625[/C][C]14155.05[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.0125671215416667[/C][C]9849371.58083333[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.11210317364672[/C][C]3138.37084820028[/C][/ROW]
[ROW][C]Covariance[/C][C]272.924598728814[/C][/ROW]
[ROW][C]Correlation[/C][C]0.762818598196512[/C][/ROW]
[ROW][C]Determination[/C][C]0.581892213754492[/C][/ROW]
[ROW][C]T-Test[/C][C]8.98444267686047[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]1.40687461680500e-12[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]7.03437308402499e-13[/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=17500&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17500&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
Mean1.31062514155.05
Biased Variance0.01256712154166679849371.58083333
Biased Standard Deviation0.112103173646723138.37084820028
Covariance272.924598728814
Correlation0.762818598196512
Determination0.581892213754492
T-Test8.98444267686047
p-value (2 sided)1.40687461680500e-12
p-value (1 sided)7.03437308402499e-13
Degrees of Freedom58
Number of Observations60


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')