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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_partialcorrelation.wasp
Title produced by softwarePartial Correlation
Date of computationWed, 12 Nov 2008 06:59:30 -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/12/t1226498406t1tmnre1zfvp7tt.htm/, Retrieved Tue, 28 May 2024 09:13:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24194, Retrieved Tue, 28 May 2024 09:13:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Testing Mean with known Variance - Type II Error] [] [2008-11-12 10:52:51] [d9be4962be2d3234142c279ef29acbcf]
F RMPD    [Partial Correlation] [] [2008-11-12 13:59:30] [8767719db498704e1fee27044c098ad0] [Current]
Feedback Forum
2008-11-20 13:37:16 [6066575aa30c0611e452e930b1dff53d] [reply] 
Het is inderdaad zo dat als we kijken naar de correlaties tussen x en y, x en z, y en z we een heel hoge correlatie zien. Maar bij deze correlaties is de derde variabele niet constant gehouden. We zien duidelijk dat wanneer de derde variabele wel constant wordt gehouden, de correlatie veel kleiner wordt. Zo zien we bijvoorbeeld dat de correlatie tussen y en z 85% bedraagt. Als x constant wordt gehouden, bedraagt deze correlatie nog maar 30%. Hierdoor kunnen we besluiten dat x een groot vertekend effect geeft.
2008-11-20 16:15:41 [Gert-Jan Geudens] [reply] 
Ik ga akkoord met de conclusie van de studente. Ik wil nog wel iets toevoegen. Aan de hand van de vergelijking tussen de correlatie (yz) en de partiële correlatie (yz,x) kunnen we opmerken dat x een zeer grote invloed heeft op de correlatie tussen de variabelen y en z.
2008-11-24 19:23:44 [4679c4d03f1d346a85e79d87ba60ec2b] [reply] 
Door de toepassing van partial correlation zie je vooral bij de correlatie tussen y en z dat er een enorme verandering ontstaat. Het is dus duidelijk dat variabele x een grote invloed uitoefent op variabele y en z. Er is inderdaad overal een lineair verband zichtbaar.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16
8
-10
-24
-19
8
24
14
7
9
-26
19
15
-1
-10
-21
-14
-27
26
23
5
19
-19
24
17
1
-9
-16
-21
-14
31
27
10
12
-23
13
26
-1
4
-16
-5
9
23
9
2
10
-29
17
9
9
-10
-23
13
13
-9
9
5
8
-18
7
4
Dataseries Y:
Download CSV
Histogram 
14
-7
-13
-11
-9
8
24
4
7
16
-30
26
19
2
-12
-29
-24
-16
25
22
-7
17
-29
18
15
1
6
-21
-23
-15
24
15
15
14
-25
14
21
13
4
-16
13
20
27
-8
13
12
-25
20
22
16
-12
-13
7
12
-8
12
-13
12
-25
0
18
Dataseries Z:
Download CSV
Histogram 
24
-6
-17
-44
-36
4
29
8
3
8
-49
32
25
-1
-20
-34
-31
-12
25
25
7
13
-40
32
14
-5
-14
-42
-24
-11
20
7
12
4
-37
19
16
2
-9
-36
-29
3
33
9
13
3
-47
18
7
16
-12
-23
-18
11
-4
17
-4
-1
-41
26
3

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=24194&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=24194&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24194&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)0.882534605336374
Partial Correlation r(xy.z)0.516642627960619
Correlation r(xz)0.891950718356225
Partial Correlation r(xz.y)0.567724457379262
Correlation r(yz)0.852582688962245
Partial Correlation r(yz.x)0.307624362258558

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Partial Correlation - Ungrouped Data \tabularnewline
Statistic & Value \tabularnewline
Correlation r(xy) & 0.882534605336374 \tabularnewline
Partial Correlation r(xy.z) & 0.516642627960619 \tabularnewline
Correlation r(xz) & 0.891950718356225 \tabularnewline
Partial Correlation r(xz.y) & 0.567724457379262 \tabularnewline
Correlation r(yz) & 0.852582688962245 \tabularnewline
Partial Correlation r(yz.x) & 0.307624362258558 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24194&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]0.882534605336374[/C][/ROW]
[ROW][C]Partial Correlation r(xy.z)[/C][C]0.516642627960619[/C][/ROW]
[ROW][C]Correlation r(xz)[/C][C]0.891950718356225[/C][/ROW]
[ROW][C]Partial Correlation r(xz.y)[/C][C]0.567724457379262[/C][/ROW]
[ROW][C]Correlation r(yz)[/C][C]0.852582688962245[/C][/ROW]
[ROW][C]Partial Correlation r(yz.x)[/C][C]0.307624362258558[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24194&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24194&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)0.882534605336374
Partial Correlation r(xy.z)0.516642627960619
Correlation r(xz)0.891950718356225
Partial Correlation r(xz.y)0.567724457379262
Correlation r(yz)0.852582688962245
Partial Correlation r(yz.x)0.307624362258558


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')