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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationMon, 20 Oct 2008 15:13:44 -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/t12245372798kyzmhphs45d8ev.htm/, Retrieved Tue, 28 May 2024 23:17:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18164, Retrieved Tue, 28 May 2024 23:17:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [Harrel Davis 95% ...] [2008-10-20 19:54:02] [5305bc6b3d76cda90639c127230e61c1]
F RMPD  [Back to Back Histogram] [BTB histogram Alg...] [2008-10-20 21:08:22] [e3bad6a1a79f69c694d9924270290d49]
F RMPD      [Pearson Correlation] [Correlation Algem...] [2008-10-20 21:13:44] [d67aed6fd81b78d9d6977a60b85d8b5e] [Current]
F    D        [Pearson Correlation] [Correlatie Algeme...] [2008-10-20 21:16:34] [5305bc6b3d76cda90639c127230e61c1]
F    D          [Pearson Correlation] [Correlatie Gezond...] [2008-10-20 21:21:23] [5305bc6b3d76cda90639c127230e61c1]
F    D            [Pearson Correlation] [Correlation Gezon...] [2008-10-20 21:24:45] [5305bc6b3d76cda90639c127230e61c1]
Feedback Forum
2008-10-27 19:01:14 [Jeroen Aerts] [reply] 
Je oplossing is correct, net als de berekening. Maar je moet wel even nadenken of dit wel een juiste conclusie is. Want ik weet niet exact wat je met Algemene index bedoelt, er staat ook geen uitleg bij. Maar je moet even logisch nadenken of deze veronderstelling wel waar kan zijn. Kan de prijs van tabak invloed hebben op de Algemene index?

Want zoals we in de les gezien hebben kan je ook toevallig op een correlatie uitkomen.
  2008-10-27 21:14:50 [Bart Haemels] [reply] 
Tabak kan zeker en vast invloed hebben op de Algemene index. Dingen zoals tabak, alcohol, Diesel deze zitten hier nog allemaal bij in. Het is daarom dat er een gezondheids index is gemaakt.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.2
2.3
2.1
2.8
3.1
2.9
2.6
2.7
2.3
2.3
2.1
2.2
2.9
2.6
2.7
1.8
1.3
0.9
1.3
1.3
1.3
1.3
1.1
1.4
1.2
1.7
1.8
1.5
1
1.6
1.5
1.8
1.8
1.6
1.9
1.7
1.6
1.3
1.1
1.9
2.6
2.3
2.4
2.2
2
2.9
2.6
2.3
2.3
2.6
3.1
2.8
2.5
2.9
3.1
3.1
3.2
2.5
2.6
2.9
Dataseries Y:
Download CSV
Histogram 
2.1
2.2
2.2
2.7
3.1
3.2
3.1
3.1
2.8
3
2.8
2.7
3.2
3.1
3
2
1.7
1.2
1.4
1.3
1.3
1.1
0.9
1.2
0.9
1.3
1.4
1.5
1.1
1.6
1.5
1.6
1.7
1.6
1.7
1.6
1.6
1.3
1.1
1.6
1.9
1.6
1.7
1.6
1.4
2.1
1.9
1.7
1.8
2
2.5
2.1
2.1
2.3
2.4
2.4
2.3
1.7
2
2.3

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=18164&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=18164&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18164&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
Mean2.123333333333331.955
Biased Variance0.4047888888888890.406141666666667
Biased Standard Deviation0.6362302168939230.637292449874205
Covariance0.322593220338983
Correlation0.78235332451912
Determination0.612076724386120
T-Test9.5663003030846
p-value (2 sided)1.56319401867222e-13
p-value (1 sided)7.8159700933611e-14
Degrees of Freedom58
Number of Observations60

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 2.12333333333333 & 1.955 \tabularnewline
Biased Variance & 0.404788888888889 & 0.406141666666667 \tabularnewline
Biased Standard Deviation & 0.636230216893923 & 0.637292449874205 \tabularnewline
Covariance & 0.322593220338983 \tabularnewline
Correlation & 0.78235332451912 \tabularnewline
Determination & 0.612076724386120 \tabularnewline
T-Test & 9.5663003030846 \tabularnewline
p-value (2 sided) & 1.56319401867222e-13 \tabularnewline
p-value (1 sided) & 7.8159700933611e-14 \tabularnewline
Degrees of Freedom & 58 \tabularnewline
Number of Observations & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18164&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]2.12333333333333[/C][C]1.955[/C][/ROW]
[ROW][C]Biased Variance[/C][C]0.404788888888889[/C][C]0.406141666666667[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]0.636230216893923[/C][C]0.637292449874205[/C][/ROW]
[ROW][C]Covariance[/C][C]0.322593220338983[/C][/ROW]
[ROW][C]Correlation[/C][C]0.78235332451912[/C][/ROW]
[ROW][C]Determination[/C][C]0.612076724386120[/C][/ROW]
[ROW][C]T-Test[/C][C]9.5663003030846[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]1.56319401867222e-13[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]7.8159700933611e-14[/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=18164&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18164&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
Mean2.123333333333331.955
Biased Variance0.4047888888888890.406141666666667
Biased Standard Deviation0.6362302168939230.637292449874205
Covariance0.322593220338983
Correlation0.78235332451912
Determination0.612076724386120
T-Test9.5663003030846
p-value (2 sided)1.56319401867222e-13
p-value (1 sided)7.8159700933611e-14
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')