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Description of Statistical Computation

Author's title

Pearson Correlation aantal inschr. nieuwe wagens - aantal inschr. 2ehandswa...

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 08:08:08 -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/t1224252629jnmafqbnegzpfdv.htm/, Retrieved Fri, 17 May 2024 11:38:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16470, Retrieved Fri, 17 May 2024 11:38:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187

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] [6fea0e9a9b3b29a63badf2c274e82506]
F    D      [Pearson Correlation] [Pearson Correlati...] [2008-10-17 14:08:08] [286e96bd53289970f8e5f25a93fb50b3] [Current]
Feedback Forum
2008-10-28 06:58:08 [An De Koninck] [reply] 
De correlatie tussen de tijdsseries werd goed uitgelegd. De student vertelt eerst wat het resultaat is die hij uit de grafiek kan aflezen en daarna vertelt hij wat dit resultaat nu net betekent.
De tijdsreeksen hangen allemaal goed samen en daarom is het erg interessant om deze met elkaar te vergelijken.
2008-10-28 08:43:20 [Michael Van Spaandonck] [reply] 
Een positieve correlatie van 77% duidt op een vrij sterk verband tussen de 2 tijdreeksen.
Waarschijnlijk zal een stijging/daling in het aantal inschrijvingen van nieuwe wagens een aanzienlijke stijging/daling in het aantal inschrijvingen van tweedehandswagens met zich meebrengen.
Goede economische tijden zullen aan de basis liggen van een stijging, aangezien de mensen hun geld kunnen en willen uitgeven, terwijl mindere economische tijden zullen leiden to afnemenede inschrijvingen omdat mensen hun geld er niet aan kunnen of willen uitgeven.
2008-11-22 15:31:36 [Jeroen Michel] [reply] 
Hier moet ik me aansluiten bij de feedback van voorgaande studenten. De student geeft een correcte grafische weergave en nadien geeft hij een correcte analyse en gebruiksmethode van deze techniek.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
Dataseries Y:
Download CSV
Histogram 
54.281
63.654
68.918
58.686
67.074
60.183
54.326
54.085
53.564
60.873
53.398
45.164
59.672
56.298
62.361
56.930
62.954
62.431
52.528
54.060
53.093
52.695
52.333
41.747
58.576
57.851
63.721
63.384
61.141
59.231
63.472
49.214
55.816
61.713
48.664
45.351
57.888
54.091
59.098
58.962
55.433
60.403
60.721
48.440
57.981
60.258
47.312
46.980
54.846
56.824
67.744
62.849
54.691
65.461
53.724
54.560
57.722
55.458
48.490
46.362

Tables (Output of Computation)





Summary of computational 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 computational 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=16470&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]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=16470&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16470&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean40.944733333333356.5956666666667
Biased Variance115.79679706222235.2590933555555
Biased Standard Deviation10.76089201981985.93793679282253
Covariance49.9877621129943
Correlation0.769273216056775
Determination0.591781280942334
T-Test9.1695526977193
p-value (2 sided)6.97220059464598e-13
p-value (1 sided)3.48610029732299e-13
Degrees of Freedom58
Number of Observations60

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 40.9447333333333 & 56.5956666666667 \tabularnewline
Biased Variance & 115.796797062222 & 35.2590933555555 \tabularnewline
Biased Standard Deviation & 10.7608920198198 & 5.93793679282253 \tabularnewline
Covariance & 49.9877621129943 \tabularnewline
Correlation & 0.769273216056775 \tabularnewline
Determination & 0.591781280942334 \tabularnewline
T-Test & 9.1695526977193 \tabularnewline
p-value (2 sided) & 6.97220059464598e-13 \tabularnewline
p-value (1 sided) & 3.48610029732299e-13 \tabularnewline
Degrees of Freedom & 58 \tabularnewline
Number of Observations & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16470&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]40.9447333333333[/C][C]56.5956666666667[/C][/ROW]
[ROW][C]Biased Variance[/C][C]115.796797062222[/C][C]35.2590933555555[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]10.7608920198198[/C][C]5.93793679282253[/C][/ROW]
[ROW][C]Covariance[/C][C]49.9877621129943[/C][/ROW]
[ROW][C]Correlation[/C][C]0.769273216056775[/C][/ROW]
[ROW][C]Determination[/C][C]0.591781280942334[/C][/ROW]
[ROW][C]T-Test[/C][C]9.1695526977193[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]6.97220059464598e-13[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]3.48610029732299e-13[/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=16470&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16470&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
Mean40.944733333333356.5956666666667
Biased Variance115.79679706222235.2590933555555
Biased Standard Deviation10.76089201981985.93793679282253
Covariance49.9877621129943
Correlation0.769273216056775
Determination0.591781280942334
T-Test9.1695526977193
p-value (2 sided)6.97220059464598e-13
p-value (1 sided)3.48610029732299e-13
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')