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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 computationFri, 17 Oct 2008 07:34:08 -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/17/t1224250558rg8w0n9dj9cpaki.htm/, Retrieved Fri, 17 May 2024 07:53:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16449, Retrieved Fri, 17 May 2024 07:53:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Harrell-Davis Quantiles] [Q7 95% confidence...] [2007-10-20 15:02:46] [b731da8b544846036771bbf9bf2f34ce]
F RMPD    [Pearson Correlation] [Pearson Correlati...] [2008-10-17 13:34:08] [286e96bd53289970f8e5f25a93fb50b3] [Current]
Feedback Forum
2008-10-28 08:24:47 [Michael Van Spaandonck] [reply] 
Een correlatie van 26% duidt inderdaad op een zwak positief verband tuissen de twee tijdreeksen.
Een stijging van de dieselprijs zal niet snel een stijging in de werkloosheid met zich meebrengen of andersom.
Misschien een enigzins nutteloze berekening.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.771
0.751
0.766
0.754
0.773
0.781
0.793
0.791
0.878
0.873
0.897
0.885
0.796
0.776
0.788
0.786
0.801
0.811
0.801
0.781
0.778
0.759
0.764
0.754
0.749
0.729
0.740
0.781
0.768
0.754
0.754
0.754
0.779
0.799
0.780
0.769
0.801
0.792
0.852
0.807
0.797
0.783
0.779
0.785
0.817
0.810
0.798
0.795
0.785
0.785
0.785
0.805
0.824
0.819
0.827
0.826
0.829
0.830
0.825
0.817
Dataseries Y:
Download CSV
Histogram 
493.000
481.000
462.000
457.000
442.000
439.000
488.000
521.000
501.000
485.000
464.000
460.000
467.000
460.000
448.000
443.000
436.000
431.000
484.000
510.000
513.000
503.000
471.000
471.000
476.000
475.000
470.000
461.000
455.000
456.000
517.000
525.000
523.000
519.000
509.000
512.000
519.000
517.000
510.000
509.000
501.000
507.000
569.000
580.000
578.000
565.000
547.000
555.000
562.000
561.000
555.000
544.000
537.000
543.000
594.000
611.000
613.000
611.000
594.000
595.000

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16449&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16449&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16449&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean0.79395510.083333333333
Biased Variance0.00118754752419.30972222222
Biased Standard Deviation0.034460811075771349.1864790590079
Covariance0.454241525423728
Correlation0.263521688571555
Determination0.0694436803476034
T-Test2.08045837016714
p-value (2 sided)0.041910839356849
p-value (1 sided)0.0209554196784245
Degrees of Freedom58
Number of Observations60

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 0.79395 & 510.083333333333 \tabularnewline
Biased Variance & 0.0011875475 & 2419.30972222222 \tabularnewline
Biased Standard Deviation & 0.0344608110757713 & 49.1864790590079 \tabularnewline
Covariance & 0.454241525423728 \tabularnewline
Correlation & 0.263521688571555 \tabularnewline
Determination & 0.0694436803476034 \tabularnewline
T-Test & 2.08045837016714 \tabularnewline
p-value (2 sided) & 0.041910839356849 \tabularnewline
p-value (1 sided) & 0.0209554196784245 \tabularnewline
Degrees of Freedom & 58 \tabularnewline
Number of Observations & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16449&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]0.79395[/C][C]510.083333333333[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.0011875475[/C][C]2419.30972222222[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.0344608110757713[/C][C]49.1864790590079[/C][/ROW]
[ROW][C]Covariance[/C][C]0.454241525423728[/C][/ROW]
[ROW][C]Correlation[/C][C]0.263521688571555[/C][/ROW]
[ROW][C]Determination[/C][C]0.0694436803476034[/C][/ROW]
[ROW][C]T-Test[/C][C]2.08045837016714[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.041910839356849[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0209554196784245[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]58[/C][/ROW]
[ROW][C]Number of Observations[/C][C]60[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16449&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16449&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
Mean0.79395510.083333333333
Biased Variance0.00118754752419.30972222222
Biased Standard Deviation0.034460811075771349.1864790590079
Covariance0.454241525423728
Correlation0.263521688571555
Determination0.0694436803476034
T-Test2.08045837016714
p-value (2 sided)0.041910839356849
p-value (1 sided)0.0209554196784245
Degrees of Freedom58
Number of Observations60


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')