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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 computationMon, 20 Oct 2008 03:27:17 -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/20/t1224494894sy3ll50az39a6z8.htm/, Retrieved Fri, 17 May 2024 09:59:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17173, Retrieved Fri, 17 May 2024 09:59:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

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] [Q4 Pearson Correl...] [2008-10-20 09:27:17] [284c7cdb9fcda2adcbb08e211682c8d6] [Current]
Feedback Forum
2008-10-27 11:34:19 [Olivier Uyttendaele] [reply] 
Berekening en interpratie zijn hier correct. Er is zo goed als geen correlatie tussen de 2 reeksen. Je ziet hier inderdaad het effect van de prijzen op de productie.

Om verder onderzoek betreffende de prijzen en correlatie te voeren, zou je eventueel de datasets uit elkaar kunnen trekken en onderzoek voeren op de correlatie van hoge prijzen en prodcutie en lage prijzen en productie

Verder kan je hier ook de P value (2sided) waarde vermelden. Deze geeft in dit geval dat er zo goed als geen toeval bestaat dat de correlatie toeval is. (0.025)

Post a new message

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 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=17173&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=17173&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17173&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
Mean86.893442622950898.111475409836
Biased Variance109.8917602794952.39249126578877
Biased Standard Deviation10.48292708548021.54676800645370
Covariance4.7317431693989
Correlation0.287034985095086
Determination0.0823890826685364
T-Test2.30160903402757
p-value (2 sided)0.0249057450545593
p-value (1 sided)0.0124528725272797
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 & 4.7317431693989 \tabularnewline
Correlation & 0.287034985095086 \tabularnewline
Determination & 0.0823890826685364 \tabularnewline
T-Test & 2.30160903402757 \tabularnewline
p-value (2 sided) & 0.0249057450545593 \tabularnewline
p-value (1 sided) & 0.0124528725272797 \tabularnewline
Degrees of Freedom & 59 \tabularnewline
Number of Observations & 61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17173&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]4.7317431693989[/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]0.0249057450545593[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0124528725272797[/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=17173&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17173&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
Covariance4.7317431693989
Correlation0.287034985095086
Determination0.0823890826685364
T-Test2.30160903402757
p-value (2 sided)0.0249057450545593
p-value (1 sided)0.0124528725272797
Degrees of Freedom59
Number of Observations61


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')