FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 12:59:41 -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/t12245292196b6c04vgvzsg93g.htm/, Retrieved Sun, 19 May 2024 12:55:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17908, Retrieved Sun, 19 May 2024 12:55:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Investigating Ass...] [2007-10-22 10:34:53] [b9964c45117f7aac638ab9056d451faa]
F RM D    [Pearson Correlation] [Pearson Tijdreeks...] [2008-10-20 18:59:41] [620b6ad5c4696049e39cb73ce029682c] [Current]
Feedback Forum
2008-10-23 19:43:12 [Ciska Tanghe] [reply] 
Aangezien we een negatieve correlatie hebben, heel dicht bij nul, kunnen we concluderen dat er weinig of geen samenhang is tussen deze twee reeksen.
2008-10-27 12:16:38 [Michael Van Spaandonck] [reply] 
Een negatieve corelatie van 0,16 duidt op een erg zwak omgekeerd lineair verband tussen wisselkoers dollar/euro en de rentevoet.

Ik ben van mening dat hierachter geen grote economische motieven schuil gaan.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,8721
0,8552
0,8564
0,8973
0,9383
0,9217
0,9095
0,892
0,8742
0,8532
0,8607
0,9005
0,9111
0,9059
0,8883
0,8924
0,8833
0,87
0,8758
0,8858
0,917
0,9554
0,9922
0,9778
0,9808
0,9811
1,0014
1,0183
1,0622
1,0773
1,0807
1,0848
1,1582
1,1663
1,1372
1,1139
1,1222
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 
4.5
4.7
4.75
4.75
4.75
4.75
4.75
4.75
4.58
4.5
4.5
4.49
4.03
3.75
3.39
3.25
3.25
3.25
3.25
3.25
3.25
3.25
3.25
3.25
3.25
3.25
3.25
2.85
2.75
2.75
2.55
2.5
2.5
2.1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2.21
2.25
2.25
2.45
2.5
2.5
2.64
2.75
2.93
3
3.17
3.25
3.39
3.5
3.5
3.65
3.75
3.75
3.9
4
4
4
4
4
4
4
4
4
4
4
4
4.18
4.25
4.25

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17908&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17908&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17908&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'Gwilym Jenkins' @ 72.249.127.135






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean1.177402061855673.09237113402062
Biased Variance0.04009057999574880.901611903496652
Biased Standard Deviation0.2002263219353260.949532465741247
Covariance-0.0321478486898625
Correlation-0.167347961416973
Determination0.0280053401904167
T-Test-1.65443721084483
p-value (2 sided)0.101339159965197
p-value (1 sided)0.0506695799825987
Degrees of Freedom95
Number of Observations97

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 1.17740206185567 & 3.09237113402062 \tabularnewline
Biased Variance & 0.0400905799957488 & 0.901611903496652 \tabularnewline
Biased Standard Deviation & 0.200226321935326 & 0.949532465741247 \tabularnewline
Covariance & -0.0321478486898625 \tabularnewline
Correlation & -0.167347961416973 \tabularnewline
Determination & 0.0280053401904167 \tabularnewline
T-Test & -1.65443721084483 \tabularnewline
p-value (2 sided) & 0.101339159965197 \tabularnewline
p-value (1 sided) & 0.0506695799825987 \tabularnewline
Degrees of Freedom & 95 \tabularnewline
Number of Observations & 97 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17908&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]1.17740206185567[/C][C]3.09237113402062[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.0400905799957488[/C][C]0.901611903496652[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.200226321935326[/C][C]0.949532465741247[/C][/ROW]
[ROW][C]Covariance[/C][C]-0.0321478486898625[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.167347961416973[/C][/ROW]
[ROW][C]Determination[/C][C]0.0280053401904167[/C][/ROW]
[ROW][C]T-Test[/C][C]-1.65443721084483[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.101339159965197[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0506695799825987[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]95[/C][/ROW]
[ROW][C]Number of Observations[/C][C]97[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17908&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17908&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
Mean1.177402061855673.09237113402062
Biased Variance0.04009057999574880.901611903496652
Biased Standard Deviation0.2002263219353260.949532465741247
Covariance-0.0321478486898625
Correlation-0.167347961416973
Determination0.0280053401904167
T-Test-1.65443721084483
p-value (2 sided)0.101339159965197
p-value (1 sided)0.0506695799825987
Degrees of Freedom95
Number of Observations97


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')