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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 07:43:56 -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/t1224251147dvtcpgs0ueeohl7.htm/, Retrieved Fri, 17 May 2024 07:54:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16454, Retrieved Fri, 17 May 2024 07:54:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181

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 13:43:56] [286e96bd53289970f8e5f25a93fb50b3] [Current]
F    D      [Pearson Correlation] [Pearson Correlati...] [2008-10-17 13:55:10] [6fea0e9a9b3b29a63badf2c274e82506]
F    D      [Pearson Correlation] [Pearson Correlati...] [2008-10-17 13:58:31] [6fea0e9a9b3b29a63badf2c274e82506]
F    D      [Pearson Correlation] [Pearson Correlati...] [2008-10-17 14:04:05] [6fea0e9a9b3b29a63badf2c274e82506]
F    D      [Pearson Correlation] [Pearson Correlati...] [2008-10-17 14:08:08] [6fea0e9a9b3b29a63badf2c274e82506]
Feedback Forum
2008-10-28 08:26:49 [Michael Van Spaandonck] [reply] 
Een negatieve correlatie van 29% duidt inderdaad op een zwak omgekeerd verband tussen de twee tijdreeksen.
Een stijging in de dieselprijs zal niet noodzakelijk een daling in het aantal inschrijvingen van nieuwe wagens met zich meebrengen of andersom.

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 
58.972
59.249
63.955
53.785
52.760
44.795
37.348
32.370
32.717
40.974
33.591
21.124
58.608
46.865
51.378
46.235
47.206
45.382
41.227
33.795
31.295
42.625
33.625
21.538
56.421
53.152
53.536
52.408
41.454
38.271
35.306
26.414
31.917
38.030
27.534
18.387
50.556
43.901
48.572
43.899
37.532
40.357
35.489
29.027
34.485
42.598
30.306
26.451
47.460
50.104
61.465
53.726
39.477
43.895
31.481
29.896
33.842
39.120
33.702
25.094

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16454&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16454&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16454&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'Gwilym Jenkins' @ 72.249.127.135






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean0.7939540.9447333333333
Biased Variance0.0011875475115.796797062222
Biased Standard Deviation0.034460811075771310.7608920198198
Covariance-0.109680166101695
Correlation-0.290840640498923
Determination0.0845882781658235
T-Test-2.31505255484162
p-value (2 sided)0.0241692659563102
p-value (1 sided)0.0120846329781551
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 & 40.9447333333333 \tabularnewline
Biased Variance & 0.0011875475 & 115.796797062222 \tabularnewline
Biased Standard Deviation & 0.0344608110757713 & 10.7608920198198 \tabularnewline
Covariance & -0.109680166101695 \tabularnewline
Correlation & -0.290840640498923 \tabularnewline
Determination & 0.0845882781658235 \tabularnewline
T-Test & -2.31505255484162 \tabularnewline
p-value (2 sided) & 0.0241692659563102 \tabularnewline
p-value (1 sided) & 0.0120846329781551 \tabularnewline
Degrees of Freedom & 58 \tabularnewline
Number of Observations & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16454&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]40.9447333333333[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.0011875475[/C][C]115.796797062222[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.0344608110757713[/C][C]10.7608920198198[/C][/ROW]
[ROW][C]Covariance[/C][C]-0.109680166101695[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.290840640498923[/C][/ROW]
[ROW][C]Determination[/C][C]0.0845882781658235[/C][/ROW]
[ROW][C]T-Test[/C][C]-2.31505255484162[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0.0241692659563102[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0.0120846329781551[/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=16454&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16454&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
Mean0.7939540.9447333333333
Biased Variance0.0011875475115.796797062222
Biased Standard Deviation0.034460811075771310.7608920198198
Covariance-0.109680166101695
Correlation-0.290840640498923
Determination0.0845882781658235
T-Test-2.31505255484162
p-value (2 sided)0.0241692659563102
p-value (1 sided)0.0120846329781551
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')