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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 computationTue, 04 Nov 2008 12:15:33 -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/04/t1225826238ow35og0bp19fvow.htm/, Retrieved Sun, 19 May 2024 05:57:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21634, Retrieved Sun, 19 May 2024 05:57:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

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 correlation] [2008-11-04 19:15:33] [3817f5e632a8bfeb1be7b5e8c86bd450] [Current]
F   P     [Partial Correlation] [Partial correlation] [2008-11-11 16:11:52] [73d6180dc45497329efd1b6934a84aba]
F   P       [Partial Correlation] [Partial Correlation] [2008-11-11 17:31:20] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
F             [Partial Correlation] [] [2008-11-11 19:37:29] [a7a7b7de998247cdf0f65ef79d563d66]
F RMP         [Trivariate Scatterplots] [] [2008-11-11 19:40:32] [a7a7b7de998247cdf0f65ef79d563d66]
-             [Partial Correlation] [] [2008-11-21 17:12:08] [888addc516c3b812dd7be4bd54caa358]
Feedback Forum
2008-11-18 19:31:36 [Glenn De Maeyer] [reply] 
Partiële correlatie onderzoekt eigenlijk in hoeverre de correlatie tussen twee tijdreeksen wordt beïnvloedt door een derde. Stel je voor je neemt de tijdreeksen x,y en z. Onder invloed van de stijging van z gaat x stijgen en onder invloed van een stijging van z gaat ook y stijgen. We krijgen dus een positief verband tussen x en y. Maar z is verantwoordelijk voor beide stijgingen. De correlatie is dus vertekend.
Als we nu hier bijvoorbeeld kijken naar de correlatie r(x,y) van x en y. Dan zien we dat deze 0.902863979754093 is. Indien we nu de partiele correlatie r(xy.z) bekijken (0.283888723977228) dan zien we dat deze een stuk lager ligt. We kunnen dus stellen dat Z hier invloed heeft op de correlatie.
2008-11-24 17:38:05 [Jan Cavents] [reply] 
op deze manier zien we hoe twee tijdsreeksen een invloed kunnen hebben op de derde. voor een voorbeeld verwijs is naar de feedback van Glenn De Maeyer

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12300.00
12092.80
12380.80
12196.90
9455.00
13168.00
13427.90
11980.50
11884.80
11691.70
12233.80
14341.40
13130.70
12421.10
14285.80
12864.60
11160.20
14316.20
14388.70
14013.90
13419.00
12769.60
13315.50
15332.90
14243.00
13824.40
14962.90
13202.90
12199.00
15508.90
14199.80
15169.60
14058.00
13786.20
14147.90
16541.70
13587.50
15582.40
15802.80
14130.50
12923.20
15612.20
16033.70
16036.60
14037.80
15330.60
15038.30
17401.80
14992.50
16043.70
16929.60
15921.30
14417.20
15961.00
17851.90
16483.90
14215.50
17429.70
17839.50
17629.20
Dataseries Y:
Download CSV
Histogram 
3423.40
3242.80
3277.20
3833.00
2606.30
3643.80
3686.40
3281.60
3669.30
3191.50
3512.70
3970.70
3601.20
3610.00
4172.10
3956.20
3142.70
3884.30
3892.20
3613.00
3730.50
3481.30
3649.50
4215.20
4066.60
4196.80
4536.60
4441.60
3548.30
4735.90
4130.60
4356.20
4159.60
3988.00
4167.80
4902.20
3909.40
4697.60
4308.90
4420.40
3544.20
4433.00
4479.70
4533.20
4237.50
4207.40
4394.00
5148.40
4202.20
4682.50
4884.30
5288.90
4505.20
4611.50
5081.10
4523.10
4412.80
4647.40
4778.60
4495.30
Dataseries Z:
Download CSV
Histogram 
15370.60
14956.90
15469.70
15101.80
11703.70
16283.60
16726.50
14968.90
14861.00
14583.30
15305.80
17903.90
16379.40
15420.30
17870.50
15912.80
13866.50
17823.20
17872.00
17420.40
16704.40
15991.20
16583.60
19123.50
17838.70
17209.40
18586.50
16258.10
15141.60
19202.10
17746.50
19090.10
18040.30
17515.50
17751.80
21072.40
17170.00
19439.50
19795.40
17574.90
16165.40
19464.60
19932.10
19961.20
17343.40
18924.20
18574.10
21350.60
18594.60
19823.10
20844.40
19640.20
17735.40
19813.60
22238.50
20682.20
17818.60
21872.10
22117.00
21865.90

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21634&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21634&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21634&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Pearson Product Moment Partial Correlation - Ungrouped Data
StatisticValue
Correlation r(xy)0.902863979754093
Partial Correlation r(xy.z)0.283888723977228
Correlation r(xz)0.997734994643543
Partial Correlation r(xz.y)0.988682211673432
Correlation r(yz)0.89643119900075
Partial Correlation r(yz.x)-0.151721858663955

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Partial Correlation - Ungrouped Data \tabularnewline
Statistic & Value \tabularnewline
Correlation r(xy) & 0.902863979754093 \tabularnewline
Partial Correlation r(xy.z) & 0.283888723977228 \tabularnewline
Correlation r(xz) & 0.997734994643543 \tabularnewline
Partial Correlation r(xz.y) & 0.988682211673432 \tabularnewline
Correlation r(yz) & 0.89643119900075 \tabularnewline
Partial Correlation r(yz.x) & -0.151721858663955 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21634&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]0.902863979754093[/C][/ROW]
[ROW][C]Partial Correlation r(xy.z)[/C][C]0.283888723977228[/C][/ROW]
[ROW][C]Correlation r(xz)[/C][C]0.997734994643543[/C][/ROW]
[ROW][C]Partial Correlation r(xz.y)[/C][C]0.988682211673432[/C][/ROW]
[ROW][C]Correlation r(yz)[/C][C]0.89643119900075[/C][/ROW]
[ROW][C]Partial Correlation r(yz.x)[/C][C]-0.151721858663955[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21634&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21634&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)0.902863979754093
Partial Correlation r(xy.z)0.283888723977228
Correlation r(xz)0.997734994643543
Partial Correlation r(xz.y)0.988682211673432
Correlation r(yz)0.89643119900075
Partial Correlation r(yz.x)-0.151721858663955


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')