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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_partialcorrelation.wasp
Title produced by softwarePartial Correlation
Date of computationFri, 07 Nov 2008 03:48:55 -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/07/t1226054989fphbqo1b16hbtm4.htm/, Retrieved Mon, 20 May 2024 03:45:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22469, Retrieved Mon, 20 May 2024 03:45:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [Various EDA topic...] [2008-11-07 10:38:01] [e5d91604aae608e98a8ea24759233f66]
F RMPD  [Trivariate Scatterplots] [Various EDA topic...] [2008-11-07 10:42:57] [e5d91604aae608e98a8ea24759233f66]
F RMPD      [Partial Correlation] [Various EDA topic...] [2008-11-07 10:48:55] [55ca0ca4a201c9689dcf5fae352c92eb] [Current]
Feedback Forum
2008-11-17 18:35:11 [8e2cc0b2ef568da46d009b2f601285b2] [reply] 
Deze gegevens leest men af als
Partial Correlation r(xz.y) 0.501025550801395

De correlatie tussen x en z gezuiverd van y. Je hebt dus zeker de juiste correlatie afgelezen. De 'Correlation r(xz)' is niet gezuiverd en geeft dan een foutief beeld.
2008-11-22 18:11:42 [Kenny Simons] [reply] 
Je moet hier niet op zoek gaan naar de hoogste correlatiewaarde.
Met deze techniek ga je op zoek naar de partiële correlatie tussen 3 variabelen. Je moet uitzoeken of de derde variabele (Z), de relatie van de eerste 2 variabelen (X, Y) al dan niet beïnvloedt.

Als de relatie tussen X,Y relatief groot is, en de partiële relatie tussen X,Y en Z is veel kleiner, dan kan je veronderstellen dat Z de relatie tussen de Xen Y beïvnloedt. 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 de partiële correlatie dicht bij de gewone correlatie ligt, kan je stellen dat de Z-variabele geen vertekend beeld geeft tussen de relatie X en Y.

2008-11-23 14:20:43 [Chi-Kwong Man] [reply] 
Deze methode vereist 3 variabelen (x,y,z). Alle correlaties worden berekend, maar voor de partiële correlatie wordt de 3de variabele gezuiverd. Hier berekent men of de 3de variabele een invloed heeft op de relatie tussen de relatie X en Y.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99.29
98.69
107.92
101.03
97.55
103.02
94.08
94.12
115.08
116.48
103.42
112.51
95.55
97.53
119.26
100.94
97.73
115.25
92.8
99.2
118.69
110.12
110.26
112.9
102.17
99.38
116.1
103.77
101.81
113.74
89.67
99.5
122.89
108.61
114.37
110.5
104.08
103.64
121.61
101.14
115.97
120.12
95.97
105.01
124.68
123.89
123.61
114.76
108.75
106.09
123.17
106.16
115.18
120.6
109.48
114.44
121.44
129.48
124.32
112.59
Dataseries Y:
Download CSV
Histogram 
1.21
1.74
1.76
1.48
1.04
1.62
1.49
1.79
1.8
1.58
1.86
1.74
1.59
1.26
1.13
1.92
2.61
2.26
2.41
2.26
2.03
2.86
2.55
2.27
2.26
2.57
3.07
2.76
2.51
2.87
3.14
3.11
3.16
2.47
2.57
2.89
2.63
2.38
1.69
1.96
2.19
1.87
1.6
1.63
1.22
1.21
1.49
1.64
1.66
1.77
1.82
1.78
1.28
1.29
1.37
1.12
1.51
2.24
2.94
3.09
Dataseries Z:
Download CSV
Histogram 
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3733.22
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22469&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22469&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22469&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Pearson Product Moment Partial Correlation - Ungrouped Data
StatisticValue
Correlation r(xy)-0.0694227592837247
Partial Correlation r(xy.z)-0.0943771828254118
Correlation r(xz)0.497933364403311
Partial Correlation r(xz.y)0.501025550801395
Correlation r(yz)0.0248973194740800
Partial Correlation r(yz.x)0.0687361546913391

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Partial Correlation - Ungrouped Data \tabularnewline
Statistic & Value \tabularnewline
Correlation r(xy) & -0.0694227592837247 \tabularnewline
Partial Correlation r(xy.z) & -0.0943771828254118 \tabularnewline
Correlation r(xz) & 0.497933364403311 \tabularnewline
Partial Correlation r(xz.y) & 0.501025550801395 \tabularnewline
Correlation r(yz) & 0.0248973194740800 \tabularnewline
Partial Correlation r(yz.x) & 0.0687361546913391 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22469&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]-0.0694227592837247[/C][/ROW]
[ROW][C]Partial Correlation r(xy.z)[/C][C]-0.0943771828254118[/C][/ROW]
[ROW][C]Correlation r(xz)[/C][C]0.497933364403311[/C][/ROW]
[ROW][C]Partial Correlation r(xz.y)[/C][C]0.501025550801395[/C][/ROW]
[ROW][C]Correlation r(yz)[/C][C]0.0248973194740800[/C][/ROW]
[ROW][C]Partial Correlation r(yz.x)[/C][C]0.0687361546913391[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22469&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22469&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)-0.0694227592837247
Partial Correlation r(xy.z)-0.0943771828254118
Correlation r(xz)0.497933364403311
Partial Correlation r(xz.y)0.501025550801395
Correlation r(yz)0.0248973194740800
Partial Correlation r(yz.x)0.0687361546913391


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')