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Description of Statistical Computation

Author's title

Partial Correlation Prijsindexcijfers grondstoffen (x), hoeveelheid uitvoer...

Author*The author of this computation has been verified*
R Software Modulerwasp_partialcorrelation.wasp
Title produced by softwarePartial Correlation
Date of computationMon, 10 Nov 2008 14:39:36 -0700
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/Nov/10/t1226353274qn3u1h1jkj8l17s.htm/, Retrieved Sun, 19 May 2024 09:25:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23209, Retrieved Sun, 19 May 2024 09:25:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Partial Correlation] [Partial Correlati...] [2008-11-10 21:39:36] [63db34dadd44fb018112addcdefe949f] [Current]
Feedback Forum
2008-11-20 22:57:54 [Olivier Uyttendaele] [reply] 
De partial correlation berekent de associatie van 3 variabelen maar je gaat ook opzoek naar de partiele correlatie.
De correlatie van de 2 variabelen X & Y van hierboven (bivariate density) noem je bijvoorbeeld de simpele correlatie r(X,Y). Bij dit model introduceer je dan een 3de variabele Z. Bedoeling hier is om te bekijken of Z -misschien wel of misschien niet- een invloed heeft de relatie tussen X & Y.

Via de partial correlation te berekenen tussen X & Y kan je dus nagaan of Z een factor is die invloed heeft Dit wordt dan r(X,Y|Z). Als r(X,Y) relatief groot is, en r(X,Y|Z) is veel kleiner, dan kan je veronderstellen dat Z een invloedrijke variabele is. Z kan dus voor een gedeelte de relatie uitleggen tussen X & Y. Het zal de relatie uitleggen maar we zullen niet te weten komen wat de relatie veroorzaakt.

Als er 3 variabelen zijn, kan je dus drie eenvoudige correlaties maken nl. r(X,Y), r(X,Z) en r(Y,Z). Wanneer je deze drie correlaties kent, kan je gemakkelijk de partiele correlatie berekenen. Vb; r (X,Z|Y).
Je zal dus telkens op deze manier bij deze de banden met de variabele wegwissen. Wanneer de partial correlation r(X,Y|Z) dicht bij de simpele correlatie ligt, dan kan gesteld worden dat Z weinig invloed heeft op de correlatie tussen X,Y.


Je probeert dus eigenlijk te onderzoeken of 1 van de reeksen invloed heeft op de correlatie van de andere reeksen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101
104
99
105
107
111
117
119
127
128
135
132
136
143
142
153
145
138
148
152
169
169
161
174
179
191
190
182
175
181
197
194
197
216
221
218
230
227
204
197
199
208
191
202
211
224
224
231
244
235
250
266
288
283
295
312
334
348
383
407
414
363
322
Dataseries Y:
Download CSV
Histogram 
105
105
109
106
82
114
118
105
105
103
107
123
112
104
122
108
94
120
118
117
113
106
108
122
115
110
120
104
96
121
111
120
114
107
108
127
105
119
121
106
97
119
122
121
106
114
112
127
109
118
123
115
105
116
131
121
104
127
126
124
132
117
123
Dataseries Z:
Download CSV
Histogram 
105
101
105
101
88
108
116
104
110
105
107
124
109
102
125
102
101
116
114
115
119
108
110
120
113
111
121
99
104
117
108
122
122
111
111
131
108
118
119
104
105
118
124
123
114
119
116
129
112
123
124
117
110
118
135
127
117
137
130
132
142
122
126

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23209&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23209&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23209&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Pearson Product Moment Partial Correlation - Ungrouped Data
StatisticValue
Correlation r(xy)0.481522451817835
Partial Correlation r(xy.z)-0.482484866728942
Correlation r(xz)0.690834097416799
Partial Correlation r(xz.y)0.691290922288206
Correlation r(yz)0.90827626302675
Partial Correlation r(yz.x)0.908392635881778

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Partial Correlation - Ungrouped Data \tabularnewline
Statistic & Value \tabularnewline
Correlation r(xy) & 0.481522451817835 \tabularnewline
Partial Correlation r(xy.z) & -0.482484866728942 \tabularnewline
Correlation r(xz) & 0.690834097416799 \tabularnewline
Partial Correlation r(xz.y) & 0.691290922288206 \tabularnewline
Correlation r(yz) & 0.90827626302675 \tabularnewline
Partial Correlation r(yz.x) & 0.908392635881778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23209&T=1

[TABLE]
[ROW][C]Pearson Product Moment Partial Correlation - Ungrouped Data[/C][/ROW]
[ROW][C]Statistic[/C][C]Value[/C][/ROW]
[ROW][C]Correlation r(xy)[/C][C]0.481522451817835[/C][/ROW]
[ROW][C]Partial Correlation r(xy.z)[/C][C]-0.482484866728942[/C][/ROW]
[ROW][C]Correlation r(xz)[/C][C]0.690834097416799[/C][/ROW]
[ROW][C]Partial Correlation r(xz.y)[/C][C]0.691290922288206[/C][/ROW]
[ROW][C]Correlation r(yz)[/C][C]0.90827626302675[/C][/ROW]
[ROW][C]Partial Correlation r(yz.x)[/C][C]0.908392635881778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23209&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23209&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 Partial Correlation - Ungrouped Data
StatisticValue
Correlation r(xy)0.481522451817835
Partial Correlation r(xy.z)-0.482484866728942
Correlation r(xz)0.690834097416799
Partial Correlation r(xz.y)0.691290922288206
Correlation r(yz)0.90827626302675
Partial Correlation r(yz.x)0.908392635881778


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
(rho12 <- cor(x, y))
(rho23 <- cor(y, z))
(rho13 <- cor(x, z))
(rhoxy_z <- (rho12-(rho13*rho23))/(sqrt(1-(rho13*rho13)) * sqrt(1-(rho23*rho23))))
(rhoxz_y <- (rho13-(rho12*rho23))/(sqrt(1-(rho12*rho12)) * sqrt(1-(rho23*rho23))))
(rhoyz_x <- (rho23-(rho12*rho13))/(sqrt(1-(rho12*rho12)) * sqrt(1-(rho13*rho13))))
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Partial Correlation - Ungrouped Data',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Value',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation r(xy)',header=TRUE)
a<-table.element(a,rho12)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('partial_correlation1.htm','Partial Correlation r(xy.z)',''),header=TRUE)
a<-table.element(a,rhoxy_z)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation r(xz)',header=TRUE)
a<-table.element(a,rho13)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('partial_correlation1.htm','Partial Correlation r(xz.y)',''),header=TRUE)
a<-table.element(a,rhoxz_y)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation r(yz)',header=TRUE)
a<-table.element(a,rho23)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('partial_correlation1.htm','Partial Correlation r(yz.x)',''),header=TRUE)
a<-table.element(a,rhoyz_x)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')