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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationThu, 30 Oct 2008 07:57:31 -0600
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/Oct/30/t1225375092xj21170u44cmfyx.htm/, Retrieved Sun, 19 May 2024 13:35:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20043, Retrieved Sun, 19 May 2024 13:35:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Pearson Correlation] [Q3 Clothing produ...] [2007-10-20 14:22:11] [b731da8b544846036771bbf9bf2f34ce]
-    D  [Pearson Correlation] [Q3 reproduce] [2008-10-20 16:49:56] [deb3c14ac9e4607a6d84fc9d0e0e6cc2]
F    D    [Pearson Correlation] [Pearson correlati...] [2008-10-30 13:52:30] [deb3c14ac9e4607a6d84fc9d0e0e6cc2]
F    D        [Pearson Correlation] [Pearson correlati...] [2008-10-30 13:57:31] [5e9e099b83e50415d7642e10d74756e4] [Current]
-    D          [Pearson Correlation] [Pearson correlati...] [2008-10-30 13:59:14] [deb3c14ac9e4607a6d84fc9d0e0e6cc2]
-    D            [Pearson Correlation] [Pearson correlati...] [2008-10-30 14:00:51] [deb3c14ac9e4607a6d84fc9d0e0e6cc2]
Feedback Forum
2008-11-06 21:10:12 [Stéphanie Van Dyck] [reply] 
De studente heeft deze vraag goed beantwoord. Maar om deze vraag op te lossen is het beter om gebruik te maken van het Kendall Tau correlation plot. Op deze grafiek kan je zien dat de laagste correlatiewaarde bij RCF ligt. Zo weet je dat er maar 1% kans bestaat dat het om een toevalligheid gaat.
2008-11-10 22:15:04 [Chi-Kwong Man] [reply] 
Vraag is goed beantwoord, maar de kendall tau methode zou het gemakkelijker en duidelijk maken. RCF is inderdaad de beste predictor.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4.8
-4.2
1.6
5.2
9.2
4.6
10.6
Dataseries Y:
Download CSV
Histogram 
20.8
17.1
22.3
25.1
27.7
24.9
29.5

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20043&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20043&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20043&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'Gwilym Jenkins' @ 72.249.127.135






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean4.5428571428571423.9142857142857
Biased Variance20.568163265306115.2355102040816
Biased Standard Deviation4.535213695660453.90326916879705
Covariance19.3042857142857
Correlation0.934718181651296
Determination0.873698079109504
T-Test5.8811291247081
p-value (2 sided)0.00201871267116260
p-value (1 sided)0.00100935633558130
Degrees of Freedom5
Number of Observations7

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 4.54285714285714 & 23.9142857142857 \tabularnewline
Biased Variance & 20.5681632653061 & 15.2355102040816 \tabularnewline
Biased Standard Deviation & 4.53521369566045 & 3.90326916879705 \tabularnewline
Covariance & 19.3042857142857 \tabularnewline
Correlation & 0.934718181651296 \tabularnewline
Determination & 0.873698079109504 \tabularnewline
T-Test & 5.8811291247081 \tabularnewline
p-value (2 sided) & 0.00201871267116260 \tabularnewline
p-value (1 sided) & 0.00100935633558130 \tabularnewline
Degrees of Freedom & 5 \tabularnewline
Number of Observations & 7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20043&T=1

[TABLE]
[ROW][C]Pearson Product Moment Correlation - Ungrouped Data[/C][/ROW]
[ROW][C]Statistic[/C][C]Variable X[/C][C]Variable Y[/C][/ROW]
[ROW][C]Mean[/C][C]4.54285714285714[/C][C]23.9142857142857[/C][/ROW]
[ROW][C]Biased Variance[/C][C]20.5681632653061[/C][C]15.2355102040816[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]4.53521369566045[/C][C]3.90326916879705[/C][/ROW]
[ROW][C]Covariance[/C][C]19.3042857142857[/C][/ROW]
[ROW][C]Correlation[/C][C]0.934718181651296[/C][/ROW]
[ROW][C]Determination[/C][C]0.873698079109504[/C][/ROW]
[ROW][C]T-Test[/C][C]5.8811291247081[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.00201871267116260[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.00100935633558130[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]5[/C][/ROW]
[ROW][C]Number of Observations[/C][C]7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20043&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20043&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 Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean4.5428571428571423.9142857142857
Biased Variance20.568163265306115.2355102040816
Biased Standard Deviation4.535213695660453.90326916879705
Covariance19.3042857142857
Correlation0.934718181651296
Determination0.873698079109504
T-Test5.8811291247081
p-value (2 sided)0.00201871267116260
p-value (1 sided)0.00100935633558130
Degrees of Freedom5
Number of Observations7


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
bitmap(file='test1.png')
histx <- hist(x, plot=FALSE)
histy <- hist(y, plot=FALSE)
maxcounts <- max(c(histx$counts, histx$counts))
xrange <- c(min(x),max(x))
yrange <- c(min(y),max(y))
nf <- layout(matrix(c(2,0,1,3),2,2,byrow=TRUE), c(3,1), c(1,3), TRUE)
par(mar=c(4,4,1,1))
plot(x, y, xlim=xrange, ylim=yrange, xlab=xlab, ylab=ylab)
par(mar=c(0,4,1,1))
barplot(histx$counts, axes=FALSE, ylim=c(0, maxcounts), space=0)
par(mar=c(4,0,1,1))
barplot(histy$counts, axes=FALSE, xlim=c(0, maxcounts), space=0, horiz=TRUE)
dev.off()
lx = length(x)
makebiased = (lx-1)/lx
varx = var(x)*makebiased
vary = var(y)*makebiased
corxy <- cor.test(x,y,method='pearson')
cxy <- as.matrix(corxy$estimate)[1,1]
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Variable X',1,TRUE)
a<-table.element(a,'Variable Y',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm','Mean',''),header=TRUE)
a<-table.element(a,mean(x))
a<-table.element(a,mean(y))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased.htm','Biased Variance',''),header=TRUE)
a<-table.element(a,varx)
a<-table.element(a,vary)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased1.htm','Biased Standard Deviation',''),header=TRUE)
a<-table.element(a,sqrt(varx))
a<-table.element(a,sqrt(vary))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('covariance.htm','Covariance',''),header=TRUE)
a<-table.element(a,cov(x,y),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('pearson_correlation.htm','Correlation',''),header=TRUE)
a<-table.element(a,cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('coeff_of_determination.htm','Determination',''),header=TRUE)
a<-table.element(a,cxy*cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ttest_statistic.htm','T-Test',''),header=TRUE)
a<-table.element(a,as.matrix(corxy$statistic)[1,1],2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (2 sided)',header=TRUE)
a<-table.element(a,(p2 <- as.matrix(corxy$p.value)[1,1]),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (1 sided)',header=TRUE)
a<-table.element(a,p2/2,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degrees of Freedom',header=TRUE)
a<-table.element(a,lx-2,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of Observations',header=TRUE)
a<-table.element(a,lx,2)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')