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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 11:55:51 -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/t1224525398pnaa54k936x2qsg.htm/, Retrieved Sun, 19 May 2024 14:59:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17802, Retrieved Sun, 19 May 2024 14:59:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126

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] [Correlation Prod....] [2008-10-20 17:55:51] [d592f629d96b926609f311957d74fcca] [Current]
Feedback Forum
2008-10-24 12:20:35 [c4ccf1f44d59ce687616256b9e80d6b0] [reply] 
Er is inderdaad sprake van een lage correlatie. Dit duidt op geen groot verband tussen de productie van kleding en de prijs. We merken op dat de punten zich concentreren boven en onderaan de grafiek. Dit duidt op een lage correlatie en zegt ons ook dat er vooral hoge en lage prijzen zijn.
2008-10-27 10:22:56 [Dorien Peeters] [reply] 
De student heeft volgens mij de juste redenering gedaan, namelijk dat er niet veel sprake is van verband tussen productie van kledij en de afzetprijsindex.
Aan de hand van deze grafiek hebben we onderzocht of er een verband is tussen de productie
van kleding en de prijs. Dit verband ontbreekt echter.
Op de grafiek zien we dat de punten totaal verspreid uit elkaar liggen. Dit wil zeggen dat
er geen correlatie of verband is tussen de gegevensreeksen.

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 time3 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 & 3 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=17802&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]3 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=17802&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17802&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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=17802&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=17802&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17802&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):
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')