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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationMon, 22 Oct 2007 01:39:33 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Oct/22/6zsxkqeqau68wuu1193043018.htm/, Retrieved Mon, 06 May 2024 06:31:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=1374, Retrieved Mon, 06 May 2024 06:31:48 +0000
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Original text written by user:Het valt op dat er een positieve correltatie is tussen de productie van kledij en de totale productie. De correlatiecoëfficiënt bedraagt namelijk 0,57. Hoe verder de coëfficiënt verwijderd is van 0, hoe nauwkeuriger we een uitspraak kunnen maken van de ene variabele op basis van de waarde van de andere variabele. Wij hadden voorspelt dat de correlatie niet perfect positief (=1) zou zijn, maar dat er wel een bepaalde positieve correlatie zou bestaan, aangezien beide producties een zekere samenhang hebben (wat logisch is).
IsPrivate?No (this computation is public)
User-defined keywordsTaak2.3G19
Estimated Impact174
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [Association Produ...] [2007-10-22 08:39:33] [6b5c00822e2ce0f7cf73539c28d95782] [Current]
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Dataseries X:
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:
110,40
96,40
101,90
106,20
81,00
94,70
101,00
109,40
102,30
90,70
96,20
96,10
106,00
103,10
102,00
104,70
86,00
92,10
106,90
112,60
101,70
92,00
97,40
97,00
105,40
102,70
98,10
104,50
87,40
89,90
109,80
111,70
98,60
96,90
95,10
97,00
112,70
102,90
97,40
111,40
87,40
96,80
114,10
110,30
103,90
101,60
94,60
95,90
104,70
102,80
98,10
113,90
80,90
95,70
113,20
105,90
108,80
102,30
99,00
100,70
115,50




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1374&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1374&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1374&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean86.8934426229508100.908196721311
Biased Variance109.89176027949564.2309164203171
Biased Standard Deviation10.48292708548028.01441928153981
Covariance48.2815546448088
Correlation0.565259717157914
Determination0.319518547841445
T-Test5.2633941884171
p-value (2 sided)2.07228182813601e-06
p-value (1 sided)1.03614091406801e-06
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 & 100.908196721311 \tabularnewline
Biased Variance & 109.891760279495 & 64.2309164203171 \tabularnewline
Biased Standard Deviation & 10.4829270854802 & 8.01441928153981 \tabularnewline
Covariance & 48.2815546448088 \tabularnewline
Correlation & 0.565259717157914 \tabularnewline
Determination & 0.319518547841445 \tabularnewline
T-Test & 5.2633941884171 \tabularnewline
p-value (2 sided) & 2.07228182813601e-06 \tabularnewline
p-value (1 sided) & 1.03614091406801e-06 \tabularnewline
Degrees of Freedom & 59 \tabularnewline
Number of Observations & 61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1374&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]100.908196721311[/C][/ROW]
[ROW][C]Biased Variance[/C][C]109.891760279495[/C][C]64.2309164203171[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]10.4829270854802[/C][C]8.01441928153981[/C][/ROW]
[ROW][C]Covariance[/C][C]48.2815546448088[/C][/ROW]
[ROW][C]Correlation[/C][C]0.565259717157914[/C][/ROW]
[ROW][C]Determination[/C][C]0.319518547841445[/C][/ROW]
[ROW][C]T-Test[/C][C]5.2633941884171[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]2.07228182813601e-06[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]1.03614091406801e-06[/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=1374&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1374&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean86.8934426229508100.908196721311
Biased Variance109.89176027949564.2309164203171
Biased Standard Deviation10.48292708548028.01441928153981
Covariance48.2815546448088
Correlation0.565259717157914
Determination0.319518547841445
T-Test5.2633941884171
p-value (2 sided)2.07228182813601e-06
p-value (1 sided)1.03614091406801e-06
Degrees of Freedom59
Number of Observations61



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')