Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationSat, 18 Oct 2008 07:41:34 -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/18/t1224337378st5z2lmx5yl9wba.htm/, Retrieved Sun, 19 May 2024 16:34:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16626, Retrieved Sun, 19 May 2024 16:34:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Eerste tijdreeks] [2008-10-11 15:49:53] [c45c87b96bbf32ffc2144fc37d767b2e]
-   PD  [Univariate Data Series] [aantal begonnen w...] [2008-10-18 13:04:32] [c45c87b96bbf32ffc2144fc37d767b2e]
F RMPD    [Pearson Correlation] [relatie tijdreeks...] [2008-10-18 13:27:30] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D      [Pearson Correlation] [relatie tijdreeks...] [2008-10-18 13:31:33] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D        [Pearson Correlation] [relatie tijdreeks...] [2008-10-18 13:35:31] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D          [Pearson Correlation] [relatie tijdreeks...] [2008-10-18 13:37:37] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D            [Pearson Correlation] [relatie tijdreeks...] [2008-10-18 13:39:20] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D                [Pearson Correlation] [relatie tijdreeks...] [2008-10-18 13:41:34] [3dc594a6c62226e1e98766c4d385bfaa] [Current]
Feedback Forum
2008-10-27 16:47:50 [Michael Van Spaandonck] [reply
Een negatieve corelatie van 82% duidt op een erg sterk omgekeerd verband tussen de twee datareeksen. De bewoonbare oppervlakte per woongelegenheid daalt naarmate er meer woongelegenheden per gebouw zijn.

Post a new message
Dataseries X:
1.61
1.25
1.21
1.42
1.22
1.42
1.44
1.44
1.48
1.49
1.59
1.33
1.51
1.36
1.45
1.44
1.32
1.40
1.35
1.50
1.52
1.45
1.45
1.59
1.49
1.35
1.70
1.52
1.36
1.44
1.56
1.61
1.73
1.58
1.50
1.51
1.73
1.52
1.60
1.41
1.46
1.58
1.41
1.61
1.31
1.62
1.51
1.60
1.61
1.63
1.46
1.87
1.92
1.62
1.50
1.43
1.64
1.62
1.68
1.82
1.68
1.50
1.75
1.78
Dataseries Y:
106.40
111.48
112.21
106.13
110.83
104.26
107.79
110.39
104.91
105.78
97.77
106.96
100.87
106.28
103.47
103.75
109.94
108.15
109.35
106.25
105.78
108.01
107.08
102.30
102.33
109.50
102.58
107.51
114.81
107.75
101.98
106.17
101.77
99.24
101.70
104.37
98.05
104.49
101.74
110.01
108.16
104.75
110.60
104.09
113.11
105.52
106.28
105.09
102.25
103.48
109.53
93.56
95.69
103.85
106.37
107.91
104.18
102.12
99.75
100.76
104.38
104.89
102.29
100.91




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16626&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16626&T=0

As an alternative you can also use a 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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean1.5228125105.1509375
Biased Variance0.0217545898437516.6261647460937
Biased Standard Deviation0.1474943722443334.07751943540356
Covariance-0.502658234126984
Correlation-0.822738626022484
Determination0.676898846749365
T-Test-11.396945664549
p-value (2 sided)7.49967074997283e-17
p-value (1 sided)3.74983537498642e-17
Degrees of Freedom62
Number of Observations64

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 1.5228125 & 105.1509375 \tabularnewline
Biased Variance & 0.02175458984375 & 16.6261647460937 \tabularnewline
Biased Standard Deviation & 0.147494372244333 & 4.07751943540356 \tabularnewline
Covariance & -0.502658234126984 \tabularnewline
Correlation & -0.822738626022484 \tabularnewline
Determination & 0.676898846749365 \tabularnewline
T-Test & -11.396945664549 \tabularnewline
p-value (2 sided) & 7.49967074997283e-17 \tabularnewline
p-value (1 sided) & 3.74983537498642e-17 \tabularnewline
Degrees of Freedom & 62 \tabularnewline
Number of Observations & 64 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16626&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]1.5228125[/C][C]105.1509375[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.02175458984375[/C][C]16.6261647460937[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.147494372244333[/C][C]4.07751943540356[/C][/ROW]
[ROW][C]Covariance[/C][C]-0.502658234126984[/C][/ROW]
[ROW][C]Correlation[/C][C]-0.822738626022484[/C][/ROW]
[ROW][C]Determination[/C][C]0.676898846749365[/C][/ROW]
[ROW][C]T-Test[/C][C]-11.396945664549[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]7.49967074997283e-17[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]3.74983537498642e-17[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]62[/C][/ROW]
[ROW][C]Number of Observations[/C][C]64[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16626&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean1.5228125105.1509375
Biased Variance0.0217545898437516.6261647460937
Biased Standard Deviation0.1474943722443334.07751943540356
Covariance-0.502658234126984
Correlation-0.822738626022484
Determination0.676898846749365
T-Test-11.396945664549
p-value (2 sided)7.49967074997283e-17
p-value (1 sided)3.74983537498642e-17
Degrees of Freedom62
Number of Observations64



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')