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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationFri, 17 Oct 2008 09:01:56 -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/17/t1224255866o88plx59nl81wkk.htm/, Retrieved Wed, 15 May 2024 19:19:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16487, Retrieved Wed, 15 May 2024 19:19:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [Q4 Clothing produ...] [2007-10-20 14:33:09] [b731da8b544846036771bbf9bf2f34ce]
F    D    [Pearson Correlation] [Overeenkomst prod...] [2008-10-17 15:01:56] [8a2d94dac8ebd598299eaec920908ca6] [Current]
Feedback Forum
2008-10-24 15:03:46 [Matthieu Blondeau] [reply] 
Hier geldt hetzelfde als voor de vorige vraag. De correlatie bedraagt 0,2... Dit wil zeggen dat er een zwak verband bestaat tussen de productie van kledij en de prijs. Dus als de prijs zou stijgen/dalen zou de productie van kledij niet noodzakelijk dezelfde beweging volgen. De student heeft dit ook aangetoond.
2008-10-27 23:05:42 [2b91075c702c6e89854c34747e80ec72] [reply] 
De interpretatie van de student is correct. Door het zwakke verband (correlatiecoëfficiënt 0,29) tussen de tijdreeksen zullen deze elkaar niet fel of zelfs helemaal niet beïnvloeden.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
109,20
88,60
94,30
98,30
86,40
80,60
104,10
108,20
93,40
71,90
94,10
94,90
96,40
91,10
84,40
86,40
88,00
75,10
109,70
103,00
82,10
68,00
96,40
94,30
90,00
88,00
76,10
82,50
81,40
66,50
97,20
94,10
80,70
70,50
87,80
89,50
99,60
84,20
75,10
92,00
80,80
73,10
99,80
90,00
83,10
72,40
78,80
87,30
91,00
80,10
73,60
86,40
74,50
71,20
92,40
81,50
85,30
69,90
84,20
90,70
100,30
Dataseries Y:
Download CSV
Histogram 
99,90
99,80
99,80
100,30
99,90
99,90
100,00
100,10
100,10
100,20
100,30
100,60
100,00
100,10
100,20
100,00
100,10
100,10
100,10
100,50
100,50
100,50
96,30
96,30
96,80
96,80
96,90
96,80
96,80
96,80
96,80
97,00
97,00
97,00
96,80
96,90
97,20
97,30
97,30
97,20
97,30
97,30
97,30
97,30
97,30
97,30
98,10
96,80
96,80
96,80
96,80
96,80
96,80
96,80
96,80
96,80
96,80
96,80
96,90
97,10
97,10

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=16487&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=16487&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16487&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 Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean86.893442622950898.111475409836
Biased Variance109.8917602794952.39249126578877
Biased Standard Deviation10.48292708548021.54676800645370
Covariance4.73174316939891
Correlation0.287034985095086
Determination0.0823890826685364
T-Test2.30160903402757
p-value (2 sided)0.0249057450545596
p-value (1 sided)0.0124528725272798
Degrees of Freedom59
Number of Observations61

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 86.8934426229508 & 98.111475409836 \tabularnewline
Biased Variance & 109.891760279495 & 2.39249126578877 \tabularnewline
Biased Standard Deviation & 10.4829270854802 & 1.54676800645370 \tabularnewline
Covariance & 4.73174316939891 \tabularnewline
Correlation & 0.287034985095086 \tabularnewline
Determination & 0.0823890826685364 \tabularnewline
T-Test & 2.30160903402757 \tabularnewline
p-value (2 sided) & 0.0249057450545596 \tabularnewline
p-value (1 sided) & 0.0124528725272798 \tabularnewline
Degrees of Freedom & 59 \tabularnewline
Number of Observations & 61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16487&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]86.8934426229508[/C][C]98.111475409836[/C][/ROW]
[ROW][C]Biased Variance[/C][C]109.891760279495[/C][C]2.39249126578877[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]10.4829270854802[/C][C]1.54676800645370[/C][/ROW]
[ROW][C]Covariance[/C][C]4.73174316939891[/C][/ROW]
[ROW][C]Correlation[/C][C]0.287034985095086[/C][/ROW]
[ROW][C]Determination[/C][C]0.0823890826685364[/C][/ROW]
[ROW][C]T-Test[/C][C]2.30160903402757[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.0249057450545596[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0124528725272798[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]59[/C][/ROW]
[ROW][C]Number of Observations[/C][C]61[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16487&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16487&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
Mean86.893442622950898.111475409836
Biased Variance109.8917602794952.39249126578877
Biased Standard Deviation10.48292708548021.54676800645370
Covariance4.73174316939891
Correlation0.287034985095086
Determination0.0823890826685364
T-Test2.30160903402757
p-value (2 sided)0.0249057450545596
p-value (1 sided)0.0124528725272798
Degrees of Freedom59
Number of Observations61


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')