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_partialcorrelation.wasp
Title produced by softwarePartial Correlation
Date of computationTue, 11 Nov 2008 07:20:55 -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/11/t122641328571v5kcvkg3a7tgl.htm/, Retrieved Sun, 19 May 2024 04:53:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23511, Retrieved Sun, 19 May 2024 04:53:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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] [Q1] [2008-11-11 14:12:08] [491a70d26f8c977398d8a0c1c87d3dd4]
F RMPD    [Partial Correlation] [Q2] [2008-11-11 14:20:55] [2ba2a74112fb2c960057a572bf2825d3] [Current]
F RMP       [Trivariate Scatterplots] [Q1] [2008-11-11 14:27:56] [491a70d26f8c977398d8a0c1c87d3dd4]
Feedback Forum
2008-11-20 17:33:25 [Steffi Van Isveldt] [reply] 
Tussen de 3 tijdreeksen is er een licht positieve correlatie te merken.
2008-11-24 13:44:48 [Siem Van Opstal] [reply] 
we merken een lichte correlatie op
2008-11-24 23:03:53 [Liese Tormans] [reply] 
De correlatie geeft het verband weer tussen twee variabele de invloed van de derde variabele is hier nog niet uitgezuiverd. Wat soms kan leiden tot een verkeerde conclusie. De oplossing voor dit probleem is de partial correlatie, deze geeft de correlatie weer tussen twee variabelen na filtering van een derde variabele. De partial correlatie gaat dan kijken welke invloed de derde variabele heeft op de eerste en de tweede variabele.
Als de gewone correlatie dicht bij de partial correlatie ligt is de invloed van de derde variabele zeer klein
Maar ligt de gewone correlatie relatief ver van de partial correlatie dan kunnen we zeggen dat de derde variabele een grote invloed heeft op de andere variabele. Bij gevolg geeft de gewone correlatie een vertekend beeld. Deze invloed kan zowel een negatief als positief zijn.

De gewone correlatie van r(xy) = 0.649868672897519
De partial correlatie r(xy.z) (na zuivering van de variabele Z) =0.370797690829168
Z heeft toch wel een invloed op X en Y: de gewone correlatie geeft een vertekend beeld

De gewone correlatie van r(xz) = 0.6492800511062
De partial correlatie r(xz.y) (na zuivering van de variabele Y) = 0.369254868314163
Y heeft toch wel een invloed op X en Z: de gewone correlatie geeft een vertekend beeld

De gewone correlatie van r(yz) = 0.684103739630612
De partial correlatie r(yz.x) (na zuivering van de variabele X) = 0.453517244762763
X heeft toch wel een invloed op Y en Z: de gewone correlatie geeft een vertekend beeld

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
109.6
103
111.6
106.3
97.9
108.8
103.9
101.2
122.9
123.9
111.7
120.9
99.6
103.3
119.4
106.5
101.9
124.6
106.5
107.8
127.4
120.1
118.5
127.7
107.7
104.5
118.8
110.3
109.6
119.1
96.5
106.7
126.3
116.2
118.8
115.2
110
111.4
129.6
108.1
117.8
122.9
100.6
111.8
127
128.6
124.8
118.5
114.7
112.6
128.7
111
115.8
126
111.1
113.2
120.1
130.6
124
119.4
116.7
Dataseries Y:
Download CSV
Histogram 
93.4
101.1
114.2
104.8
113.3
118.2
83.6
73.9
99.5
97.7
103
106.3
92.2
101.8
122.8
111.8
106.3
121.5
81.9
85.4
110.9
117.3
106.3
105.6
101.2
105.9
126.3
111.9
108.9
127.2
94.2
85.7
116.2
107.2
110.5
112
104.4
112
132.8
110.8
128.7
136.8
94.8
88.8
123.2
125.3
122.7
125.8
116.3
118.6
142.1
127.9
132
152.4
110.8
99.1
134.9
133.2
131
133.9
119.9
Dataseries Z:
Download CSV
Histogram 
97.6
99.5
110.7
104.4
99.8
108.4
91.8
90.2
109.2
111.4
102.8
91.5
98.9
100.8
112.1
106.7
103.5
111.3
100.8
94.2
115.5
114.1
105
94
98.3
96
101.8
102.5
98.7
110.7
88.7
89.2
106.8
104.1
103.2
93.7
100.5
98.7
111.1
104.5
105
109.7
92.6
94.2
111.7
113.4
106.8
98
104.2
105.4
117.5
107.9
107
113.3
97.6
98.2
111.3
116
108.1
95.6
110.8

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=23511&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=23511&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23511&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 Partial Correlation - Ungrouped Data
StatisticValue
Correlation r(xy)0.649868672897519
Partial Correlation r(xy.z)0.370797690829168
Correlation r(xz)0.6492800511062
Partial Correlation r(xz.y)0.369254868314163
Correlation r(yz)0.684103739630612
Partial Correlation r(yz.x)0.453517244762763

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Partial Correlation - Ungrouped Data \tabularnewline
Statistic & Value \tabularnewline
Correlation r(xy) & 0.649868672897519 \tabularnewline
Partial Correlation r(xy.z) & 0.370797690829168 \tabularnewline
Correlation r(xz) & 0.6492800511062 \tabularnewline
Partial Correlation r(xz.y) & 0.369254868314163 \tabularnewline
Correlation r(yz) & 0.684103739630612 \tabularnewline
Partial Correlation r(yz.x) & 0.453517244762763 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23511&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]0.649868672897519[/C][/ROW]
[ROW][C]Partial Correlation r(xy.z)[/C][C]0.370797690829168[/C][/ROW]
[ROW][C]Correlation r(xz)[/C][C]0.6492800511062[/C][/ROW]
[ROW][C]Partial Correlation r(xz.y)[/C][C]0.369254868314163[/C][/ROW]
[ROW][C]Correlation r(yz)[/C][C]0.684103739630612[/C][/ROW]
[ROW][C]Partial Correlation r(yz.x)[/C][C]0.453517244762763[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23511&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23511&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)0.649868672897519
Partial Correlation r(xy.z)0.370797690829168
Correlation r(xz)0.6492800511062
Partial Correlation r(xz.y)0.369254868314163
Correlation r(yz)0.684103739630612
Partial Correlation r(yz.x)0.453517244762763


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')