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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 07:52:28 -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/t1224510825z6bubt19i9kidlk.htm/, Retrieved Fri, 17 May 2024 09:31:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17288, Retrieved Fri, 17 May 2024 09:31:51 +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] [Q5 Relationship b...] [2007-10-20 14:40:02] [b731da8b544846036771bbf9bf2f34ce]
F    D    [Pearson Correlation] [Samenhang product...] [2008-10-20 13:52:28] [de3f0516a1536f7c4a656924d8bc8d07] [Current]
Feedback Forum
2008-10-25 12:39:46 [Davy De Nef] [reply] 
De correlatie tussen de 2 reeksen is klein. Dit komt hoofdzakelijk door de outlier linksboven. Als we deze zouden weglaten, kunnen we een denkbeeldige stijgende rechte tekenen door de overige punten. Dat resulteert in een duidelijke positieve correlatie.
2008-10-25 13:35:24 [Astrid Sniekers] [reply] 
We hebben hier te maken met een kleine positieve correlatie, omdat 2 ‘outliers’ de correlatie helemaal verpesten. Dit kunnen we afleiden aan de hand van de grafiek. Dit heeft de student spijtig genoeg niet opgemerkt.
2008-10-26 16:32:34 [Kristof Augustyns] [reply] 
Een samenhang van 4% tussen de kleding productie en investeringen.
Bij afronding kan men dit dus feitelijk brengen tot 0% en dus vrijwel totaal geen samenhang.
Die twee beïnvloeden elkaar dus voor een schamele 4%.
Het is dus niet zo dat als de kleding productie zou stijgen, de investeringen ook stijgen.
De student hier heeft niet opgemerkt of niet vermeld dat die twee puntjes links bovenaan de verpesters zijn.
Hadden die twee puntjes (waarschijnlijk outliers) er niet geweest, kon men een mooie licht stijgende rechte trekken van de linkse onderhoek naar rechts.
Zo zou de correlatie toch wel een stuk hoger hebben gelegen.
Het is dus eigelijk door die twee verziekers (puntjes) dat er vrijwel geen samenhang is tussen kleding productie en de investeringen.
Dus ook weer veel te weinig uitleg aan het adres van deze student.
2008-10-27 11:03:57 [Thomas Beyers] [reply] 
Het zijn de outliers die de scatterplot beïnvloeden.

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 
72.50
59.40
85.70
88.20
62.80
87.00
79.20
112.00
79.20
132.10
40.10
69.00
59.40
73.80
57.40
81.10
46.60
41.40
71.20
67.90
72.00
145.50
39.70
51.90
73.70
70.90
60.80
61.00
54.50
39.10
66.60
58.50
59.80
80.90
37.30
44.60
48.70
54.00
49.50
61.60
35.00
35.70
51.30
49.00
41.50
72.50
42.10
44.10
45.10
50.30
40.90
47.20
36.90
40.90
38.30
46.30
28.40
78.40
36.80
50.70
42.80

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=17288&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=17288&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17288&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
Mean86.893442622950859.8491803278689
Biased Variance109.891760279495494.798892770761
Biased Standard Deviation10.482927085480222.2440754532698
Covariance10.0804945355191
Correlation0.0425212799870432
Determination0.00180805925173652
T-Test0.326907817024733
p-value (2 sided)0.744894582950823
p-value (1 sided)0.372447291475412
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 & 59.8491803278689 \tabularnewline
Biased Variance & 109.891760279495 & 494.798892770761 \tabularnewline
Biased Standard Deviation & 10.4829270854802 & 22.2440754532698 \tabularnewline
Covariance & 10.0804945355191 \tabularnewline
Correlation & 0.0425212799870432 \tabularnewline
Determination & 0.00180805925173652 \tabularnewline
T-Test & 0.326907817024733 \tabularnewline
p-value (2 sided) & 0.744894582950823 \tabularnewline
p-value (1 sided) & 0.372447291475412 \tabularnewline
Degrees of Freedom & 59 \tabularnewline
Number of Observations & 61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17288&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]59.8491803278689[/C][/ROW]
[ROW][C]Biased Variance[/C][C]109.891760279495[/C][C]494.798892770761[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]10.4829270854802[/C][C]22.2440754532698[/C][/ROW]
[ROW][C]Covariance[/C][C]10.0804945355191[/C][/ROW]
[ROW][C]Correlation[/C][C]0.0425212799870432[/C][/ROW]
[ROW][C]Determination[/C][C]0.00180805925173652[/C][/ROW]
[ROW][C]T-Test[/C][C]0.326907817024733[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.744894582950823[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.372447291475412[/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=17288&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17288&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
Mean86.893442622950859.8491803278689
Biased Variance109.891760279495494.798892770761
Biased Standard Deviation10.482927085480222.2440754532698
Covariance10.0804945355191
Correlation0.0425212799870432
Determination0.00180805925173652
T-Test0.326907817024733
p-value (2 sided)0.744894582950823
p-value (1 sided)0.372447291475412
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')