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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSun, 12 Dec 2010 20:39:50 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/12/t1292186335ot8n7vcempyczoz.htm/, Retrieved Wed, 08 May 2024 03:16:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108672, Retrieved Wed, 08 May 2024 03:16:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Kendall tau Correlation Matrix] [Workshop 10 Kenda...] [2010-12-12 20:39:50] [4c92126b39409bf78ea2674c8170c829] [Current]
F   P     [Kendall tau Correlation Matrix] [Workshop 10] [2010-12-12 20:45:49] [ec8d68d52c1e9c5e97bb689b42436a8c]
F RMP     [Multiple Regression] [WS10] [2010-12-12 20:48:33] [ebb35fb07def4d07c0eb7ec8d2fd3b0e]
F RMP     [Recursive Partitioning (Regression Trees)] [WS10] [2010-12-12 20:51:22] [ec8d68d52c1e9c5e97bb689b42436a8c]
F RMP     [Recursive Partitioning (Regression Trees)] [ws10] [2010-12-12 20:55:40] [ebb35fb07def4d07c0eb7ec8d2fd3b0e]
Feedback Forum
2010-12-15 19:04:48 [Pascal Wijnen] [reply
De student begint met een juiste methode, enkel is hier het probleem dat er bij deze methode een normaal-verdeling aanwezig MOET zijn, dit is niet het geval. De output van dit model is dus eigenlijk niet bruikbaar voor de probleemstelling van de student. De student geeft hier ook geen enkele verklaring van de bereikte gegevens of interpretatie!

Post a new message
Dataseries X:
12008.00	4.00
9169.00	5.90
8788.00	7.10
8417.00	10.50
8247.00	15.10
8197.00	16.80
8236.00	15.30
8253.00	18.40
7733.00	16.10
8366.00	11.30
8626.00	7.90
8863.00	5.60
10102.00	3.40
8463.00	4.80
9114.00	6.50
8563.00	8.50
8872.00	15.10
8301.00	15.70
8301.00	18.70
8278.00	19.20
7736.00	12.90
7973.00	14.40
8268.00	6.20
9476.00	3.30
11100.00	4.60
8962.00	7.10
9173.00	7.80
8738.00	9.90
8459.00	13.60
8078.00	17.10
8411.00	17.80
8291.00	18.60
7810.00	14.70
8616.00	10.50
8312.00	8.60
9692.00	4.40
9911.00	2.30
8915.00	2.80
9452.00	8.80
9112.00	10.70
8472.00	13.90
8230.00	19.30
8384.00	19.50
8625.00	20.40
8221.00	15.30
8649.00	7.90
8625.00	8.30
10443.00	4.50
10357.00	3.20
8586.00	5.00
8892.00	6.60
8329.00	11.10
8101.00	12.80
7922.00	16.30
8120.00	17.40
7838.00	18.90
7735.00	15.80
8406.00	11.70
8209.00	6.40
9451.00	2.90
10041.00	4.70
9411.00	2.40
10405.00	7.20
8467.00	10.70
8464.00	13.40
8102.00	18.30
7627.00	18.40
7513.00	16.80
7510.00	16.60
8291.00	14.10
8064.00	6.10
9383.00	3.50
9706.00	1.70
8579.00	2.30
9474.00	4.50
8318.00	9.30
8213.00	14.20
8059.00	17.30
9111.00	23.00
7708.00	16.30
7680.00	18.40
8014.00	14.20
8007.00	9.10
8718.00	5.90
9486.00	7.20
9113.00	6.80
9025.00	8.00
8476.00	14.30
7952.00	14.60
7759.00	17.50
7835.00	17.20
7600.00	17.20
7651.00	14.10
8319.00	10.40
8812.00	6.80
8630.00	4.10




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=108672&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=108672&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108672&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=pearson)
SterftegevallenTemperatuur
Sterftegevallen1-0.671
Temperatuur-0.6711

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Sterftegevallen & Temperatuur \tabularnewline
Sterftegevallen & 1 & -0.671 \tabularnewline
Temperatuur & -0.671 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108672&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Sterftegevallen[/C][C]Temperatuur[/C][/ROW]
[ROW][C]Sterftegevallen[/C][C]1[/C][C]-0.671[/C][/ROW]
[ROW][C]Temperatuur[/C][C]-0.671[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108672&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108672&T=1

As an alternative you can also use a QR Code:  

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

Correlations for all pairs of data series (method=pearson)
SterftegevallenTemperatuur
Sterftegevallen1-0.671
Temperatuur-0.6711







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Sterftegevallen;Temperatuur-0.6712-0.7231-0.5254
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Sterftegevallen;Temperatuur & -0.6712 & -0.7231 & -0.5254 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108672&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]Sterftegevallen;Temperatuur[/C][C]-0.6712[/C][C]-0.7231[/C][C]-0.5254[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108672&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108672&T=2

As an alternative you can also use a QR Code:  

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

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Sterftegevallen;Temperatuur-0.6712-0.7231-0.5254
p-value(0)(0)(0)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')