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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 16:07:50 -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/21/t1224540506psbn8udiyaaqcuf.htm/, Retrieved Fri, 17 May 2024 03:06:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18237, Retrieved Fri, 17 May 2024 03:06:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

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] [Q3 Clothing produ...] [2007-10-20 14:22:11] [b731da8b544846036771bbf9bf2f34ce]
F    D    [Pearson Correlation] [Correlatie clothi...] [2008-10-20 22:07:50] [02e7fb326979b65614900650d62c19a6] [Current]
Feedback Forum
2008-10-26 11:42:27 [Lindsay Heyndrickx] [reply] 
De correlatie moet tusssen 1, nul en -1 liggen. 0.57 ligt hier perfect tussen nul en 1 dus je hebt hier correlatie. Als je naar de grafiek gaat kijken zie je dat je een stijgende rechten kan tekenen tussen de puntjes. Dus hier heb je te maken met een positieve correlatie. Hier is sprake van een gemiddelde correlatie
2008-10-26 11:49:31 [Lindsay Heyndrickx] [reply] 
De vorige feedback hoort bij q5
dit antwoord hoort bij q6:
De conclusie die de student hier trekt is volledig juist maar de blog is volledig verkeerd. Hij heeft hier de correlatie berekend en deze methode moet berekend worden met percentiels of met harrel Davis. Hier kan je met percentiels werken omdat je de stepsize hier niet moet aanpassen die staat hier al automatisch op 0.01. daarom kan je hier de percientiels nog gebruiken.
2008-10-26 21:26:44 [Stéphanie Thijs] [reply] 
Q3: Gaat niet over wat de reeksen gemeenschappelijk hebben met elkaar, maar over de invloed die ze op elkaar hebben. Kledingproductie en totale productie zijn gemiddeld afhankelijk van elkaar (een positieve correlatie van bijna 57%).
2008-10-26 21:35:12 [Stéphanie Thijs] [reply] 
Deze link wordt zowel bij Q3 als bij Q6 gegeven. Hoort absoluut niet bij Q6, moest een Harrel-Davis-quantiles berekening zijn.

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 
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

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=18237&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=18237&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18237&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
Mean86.8934426229508100.908196721311
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=18237&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=18237&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18237&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
Mean86.8934426229508100.908196721311
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


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')