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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationThu, 08 Dec 2011 17:58:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/08/t1323385102cvh1zh9wbwdl4tl.htm/, Retrieved Fri, 03 May 2024 07:56:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153181, Retrieved Fri, 03 May 2024 07:56:20 +0000
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Estimated Impact83
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2011-12-08 22:58:04] [13d85cac30d4a10947636c080219d4f4] [Current]
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Dataseries X:
57.59	33306600	23.42	2120.30	0.0435
67.82	23898100	25.30	2232.82	0.0346
71.89	23279600	23.90	2205.32	0.0342
75.51	40699800	25.73	2305.82	0.0399
68.49	37646000	24.64	2281.39	0.036
62.72	37277000	24.95	2339.79	0.0336
70.39	39246800	22.15	2322.57	0.0355
59.77	27418400	20.85	2178.88	0.0417
57.27	30318700	21.45	2172.09	0.0432
67.96	32808100	22.15	2091.47	0.0415
67.85	28668200	23.75	2183.75	0.0382
76.98	32370300	25.27	2258.43	0.0206
81.08	24171100	26.53	2366.71	0.0131
91.66	25009100	27.22	2431.77	0.0197
84.84	32084300	27.69	2415.29	0.0254
85.73	50117500	28.61	2463.93	0.0208
84.61	27522200	26.21	2416.15	0.0242
92.91	26816800	25.93	2421.64	0.0278
99.80	25136100	27.86	2525.09	0.0257
121.19	30295600	28.65	2604.52	0.0269
122.04	41526100	27.51	2603.23	0.0269
131.76	43845100	27.06	2546.27	0.0236
138.48	39188900	26.91	2596.36	0.0197
153.47	40496400	27.60	2701.50	0.0276
189.95	37438400	34.48	2859.12	0.0354
182.22	46553700	31.58	2660.96	0.0431
198.08	31771400	33.46	2652.28	0.0408
135.36	62108100	30.64	2389.86	0.0428
125.02	46645400	25.66	2271.48	0.0403
143.50	42313100	26.78	2279.10	0.0398
173.95	38841700	26.91	2412.80	0.0394
188.75	32650300	26.82	2522.66	0.0418
167.44	34281100	26.05	2292.98	0.0502
158.95	33096200	24.36	2325.55	0.056
169.53	23273800	25.94	2367.52	0.0537
113.66	43697600	25.37	2091.88	0.0494
107.59	66902300	21.23	1720.95	0.0366
92.67	44957200	19.35	1535.57	0.0107
85.35	33800900	18.61	1577.03	0.0009
90.13	33487900	16.37	1476.42	0.0003
89.31	27394900	15.56	1377.84	0.0024
105.12	25963400	17.70	1528.59	-0.0038
125.83	20952600	19.52	1717.30	-0.0074
135.81	17702900	20.26	1774.33	-0.0128
142.43	21282100	23.05	1835.04	-0.0143
163.39	18449100	22.81	1978.50	-0.021
168.21	14415700	24.04	2009.06	-0.0148
185.35	17906300	25.08	2122.42	-0.0129
188.50	22197500	27.04	2045.11	-0.0018
199.91	15856500	28.81	2144.60	0.0184
210.73	19068700	29.86	2269.15	0.0272
192.06	30855100	27.61	2147.35	0.0263
204.62	21209000	28.22	2238.26	0.0214
235.00	19541600	28.83	2397.96	0.0231
261.09	21955000	30.06	2461.19	0.0224
256.88	33725900	25.51	2257.04	0.0202
251.53	28192800	22.75	2109.24	0.0105
257.25	27377000	25.52	2254.70	0.0124
243.10	16228100	23.33	2114.03	0.0115
283.75	21278900	24.34	2368.62	0.0114




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153181&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153181&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153181&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'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=kendall)
APPLEVOLUMEMICROSOFTNASDAQINFLATION
APPLE1-0.1940.2980.134-0.184
VOLUME-0.19410.0680.2010.362
MICROSOFT0.2980.06810.6250.164
NASDAQ0.1340.2010.62510.269
INFLATION-0.1840.3620.1640.2691

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & APPLE & VOLUME & MICROSOFT & NASDAQ & INFLATION \tabularnewline
APPLE & 1 & -0.194 & 0.298 & 0.134 & -0.184 \tabularnewline
VOLUME & -0.194 & 1 & 0.068 & 0.201 & 0.362 \tabularnewline
MICROSOFT & 0.298 & 0.068 & 1 & 0.625 & 0.164 \tabularnewline
NASDAQ & 0.134 & 0.201 & 0.625 & 1 & 0.269 \tabularnewline
INFLATION & -0.184 & 0.362 & 0.164 & 0.269 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153181&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]APPLE[/C][C]VOLUME[/C][C]MICROSOFT[/C][C]NASDAQ[/C][C]INFLATION[/C][/ROW]
[ROW][C]APPLE[/C][C]1[/C][C]-0.194[/C][C]0.298[/C][C]0.134[/C][C]-0.184[/C][/ROW]
[ROW][C]VOLUME[/C][C]-0.194[/C][C]1[/C][C]0.068[/C][C]0.201[/C][C]0.362[/C][/ROW]
[ROW][C]MICROSOFT[/C][C]0.298[/C][C]0.068[/C][C]1[/C][C]0.625[/C][C]0.164[/C][/ROW]
[ROW][C]NASDAQ[/C][C]0.134[/C][C]0.201[/C][C]0.625[/C][C]1[/C][C]0.269[/C][/ROW]
[ROW][C]INFLATION[/C][C]-0.184[/C][C]0.362[/C][C]0.164[/C][C]0.269[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153181&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153181&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=kendall)
APPLEVOLUMEMICROSOFTNASDAQINFLATION
APPLE1-0.1940.2980.134-0.184
VOLUME-0.19410.0680.2010.362
MICROSOFT0.2980.06810.6250.164
NASDAQ0.1340.2010.62510.269
INFLATION-0.1840.3620.1640.2691







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
APPLE;VOLUME-0.2939-0.3015-0.1944
p-value(0.0226)(0.0196)(0.0282)
APPLE;MICROSOFT0.38580.41780.2985
p-value(0.0023)(9e-04)(8e-04)
APPLE;NASDAQ0.20650.14470.1345
p-value(0.1135)(0.2692)(0.129)
APPLE;INFLATION-0.184-0.2422-0.1843
p-value(0.1594)(0.0623)(0.0376)
VOLUME;MICROSOFT0.11550.09910.0678
p-value(0.3794)(0.4514)(0.444)
VOLUME;NASDAQ0.15510.29790.2011
p-value(0.2366)(0.0212)(0.0232)
VOLUME;INFLATION0.49980.52130.3618
p-value(0)(0)(0)
MICROSOFT;NASDAQ0.86180.78250.6252
p-value(0)(0)(0)
MICROSOFT;INFLATION0.3980.26480.164
p-value(0.0016)(0.0409)(0.0643)
NASDAQ;INFLATION0.53480.41550.2691
p-value(0)(0.001)(0.0024)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
APPLE;VOLUME & -0.2939 & -0.3015 & -0.1944 \tabularnewline
p-value & (0.0226) & (0.0196) & (0.0282) \tabularnewline
APPLE;MICROSOFT & 0.3858 & 0.4178 & 0.2985 \tabularnewline
p-value & (0.0023) & (9e-04) & (8e-04) \tabularnewline
APPLE;NASDAQ & 0.2065 & 0.1447 & 0.1345 \tabularnewline
p-value & (0.1135) & (0.2692) & (0.129) \tabularnewline
APPLE;INFLATION & -0.184 & -0.2422 & -0.1843 \tabularnewline
p-value & (0.1594) & (0.0623) & (0.0376) \tabularnewline
VOLUME;MICROSOFT & 0.1155 & 0.0991 & 0.0678 \tabularnewline
p-value & (0.3794) & (0.4514) & (0.444) \tabularnewline
VOLUME;NASDAQ & 0.1551 & 0.2979 & 0.2011 \tabularnewline
p-value & (0.2366) & (0.0212) & (0.0232) \tabularnewline
VOLUME;INFLATION & 0.4998 & 0.5213 & 0.3618 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
MICROSOFT;NASDAQ & 0.8618 & 0.7825 & 0.6252 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
MICROSOFT;INFLATION & 0.398 & 0.2648 & 0.164 \tabularnewline
p-value & (0.0016) & (0.0409) & (0.0643) \tabularnewline
NASDAQ;INFLATION & 0.5348 & 0.4155 & 0.2691 \tabularnewline
p-value & (0) & (0.001) & (0.0024) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153181&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]APPLE;VOLUME[/C][C]-0.2939[/C][C]-0.3015[/C][C]-0.1944[/C][/ROW]
[ROW][C]p-value[/C][C](0.0226)[/C][C](0.0196)[/C][C](0.0282)[/C][/ROW]
[ROW][C]APPLE;MICROSOFT[/C][C]0.3858[/C][C]0.4178[/C][C]0.2985[/C][/ROW]
[ROW][C]p-value[/C][C](0.0023)[/C][C](9e-04)[/C][C](8e-04)[/C][/ROW]
[ROW][C]APPLE;NASDAQ[/C][C]0.2065[/C][C]0.1447[/C][C]0.1345[/C][/ROW]
[ROW][C]p-value[/C][C](0.1135)[/C][C](0.2692)[/C][C](0.129)[/C][/ROW]
[ROW][C]APPLE;INFLATION[/C][C]-0.184[/C][C]-0.2422[/C][C]-0.1843[/C][/ROW]
[ROW][C]p-value[/C][C](0.1594)[/C][C](0.0623)[/C][C](0.0376)[/C][/ROW]
[ROW][C]VOLUME;MICROSOFT[/C][C]0.1155[/C][C]0.0991[/C][C]0.0678[/C][/ROW]
[ROW][C]p-value[/C][C](0.3794)[/C][C](0.4514)[/C][C](0.444)[/C][/ROW]
[ROW][C]VOLUME;NASDAQ[/C][C]0.1551[/C][C]0.2979[/C][C]0.2011[/C][/ROW]
[ROW][C]p-value[/C][C](0.2366)[/C][C](0.0212)[/C][C](0.0232)[/C][/ROW]
[ROW][C]VOLUME;INFLATION[/C][C]0.4998[/C][C]0.5213[/C][C]0.3618[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MICROSOFT;NASDAQ[/C][C]0.8618[/C][C]0.7825[/C][C]0.6252[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MICROSOFT;INFLATION[/C][C]0.398[/C][C]0.2648[/C][C]0.164[/C][/ROW]
[ROW][C]p-value[/C][C](0.0016)[/C][C](0.0409)[/C][C](0.0643)[/C][/ROW]
[ROW][C]NASDAQ;INFLATION[/C][C]0.5348[/C][C]0.4155[/C][C]0.2691[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.001)[/C][C](0.0024)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153181&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153181&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
APPLE;VOLUME-0.2939-0.3015-0.1944
p-value(0.0226)(0.0196)(0.0282)
APPLE;MICROSOFT0.38580.41780.2985
p-value(0.0023)(9e-04)(8e-04)
APPLE;NASDAQ0.20650.14470.1345
p-value(0.1135)(0.2692)(0.129)
APPLE;INFLATION-0.184-0.2422-0.1843
p-value(0.1594)(0.0623)(0.0376)
VOLUME;MICROSOFT0.11550.09910.0678
p-value(0.3794)(0.4514)(0.444)
VOLUME;NASDAQ0.15510.29790.2011
p-value(0.2366)(0.0212)(0.0232)
VOLUME;INFLATION0.49980.52130.3618
p-value(0)(0)(0)
MICROSOFT;NASDAQ0.86180.78250.6252
p-value(0)(0)(0)
MICROSOFT;INFLATION0.3980.26480.164
p-value(0.0016)(0.0409)(0.0643)
NASDAQ;INFLATION0.53480.41550.2691
p-value(0)(0.001)(0.0024)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
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')