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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 09:42:20 -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/t122451737558oywpw1isu0ip7.htm/, Retrieved Sun, 19 May 2024 15:23:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17513, Retrieved Sun, 19 May 2024 15:23:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

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] [associatie kledin...] [2008-10-20 15:42:20] [28deb8481dba3cc87d2d53a86e0e0d0b] [Current]
Feedback Forum
2008-10-25 11:09:29 [Kevin Truyts] [reply] 
Dit maal heeft de student 2 verschillende data sets genomen, maar hij heeft in tegenstelling tot de titel een vergelijking (correlatie) gemaakt tussen de totale productie en de prijs, i.p.v. tussen de productie van kledij en prijs.
We stellen vast dat als we grafisch gaan vergelijken, de grafieken ongeveer overeenkomen (beide hebben zowel boven als onder punten en niet in het midden). Maar wanneer we naar de correlatiecoëfficiënt gaan kijken, zien we een negatieve coëfficiënt (-0.097) t.o.v. een positieve (0.287).

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Oct/18/t12243470560wvjn9wq0fgqetd.htm, Retrieved Sat, 18 Oct 2008 16:24:25 +0000
2008-10-25 12:08:58 [Bob Leysen] [reply] 
De opdracht was een vergelijking te maken tussen de productie van kledij en prijs. Het juiste antwoord is een correlatie van 0,2870 en dat betekent een zwak verband tussen de 2 datasets.
2008-10-27 17:28:19 [Bob Leysen] [reply] 
Hieronder de correcte link:

http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/20/t12244585458k4ao5b7vu6022p.htm

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
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 time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17513&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]4 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=17513&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17513&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean100.90819672131198.111475409836
Biased Variance64.23091642031712.39249126578877
Biased Standard Deviation8.014419281539811.54676800645370
Covariance-1.22776229508197
Correlation-0.0974178336509467
Determination0.00949023431324353
T-Test-0.751856731851351
p-value (2 sided)0.455126176098772
p-value (1 sided)0.227563088049386
Degrees of Freedom59
Number of Observations61

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 100.908196721311 & 98.111475409836 \tabularnewline
Biased Variance & 64.2309164203171 & 2.39249126578877 \tabularnewline
Biased Standard Deviation & 8.01441928153981 & 1.54676800645370 \tabularnewline
Covariance & -1.22776229508197 \tabularnewline
Correlation & -0.0974178336509467 \tabularnewline
Determination & 0.00949023431324353 \tabularnewline
T-Test & -0.751856731851351 \tabularnewline
p-value (2 sided) & 0.455126176098772 \tabularnewline
p-value (1 sided) & 0.227563088049386 \tabularnewline
Degrees of Freedom & 59 \tabularnewline
Number of Observations & 61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17513&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]100.908196721311[/C][C]98.111475409836[/C][/ROW]
[ROW][C]Biased Variance[/C][C]64.2309164203171[/C][C]2.39249126578877[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]8.01441928153981[/C][C]1.54676800645370[/C][/ROW]
[ROW][C]Covariance[/C][C]-1.22776229508197[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.0974178336509467[/C][/ROW]
[ROW][C]Determination[/C][C]0.00949023431324353[/C][/ROW]
[ROW][C]T-Test[/C][C]-0.751856731851351[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.455126176098772[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.227563088049386[/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=17513&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17513&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
Mean100.90819672131198.111475409836
Biased Variance64.23091642031712.39249126578877
Biased Standard Deviation8.014419281539811.54676800645370
Covariance-1.22776229508197
Correlation-0.0974178336509467
Determination0.00949023431324353
T-Test-0.751856731851351
p-value (2 sided)0.455126176098772
p-value (1 sided)0.227563088049386
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')