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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 computationTue, 20 Dec 2011 17:16:44 -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/20/t13244194122xtquzwoeml40p3.htm/, Retrieved Sun, 05 May 2024 22:56:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158314, Retrieved Sun, 05 May 2024 22:56:01 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2011-12-20 22:16:44] [d9117990bcd7292ecd0ccf87cb78a2ce] [Current]
- R  D    [Kendall tau Correlation Matrix] [paper deel 3 pear...] [2011-12-22 23:54:24] [d5821fed422662f85834b1edae505ce2]
-   P       [Kendall tau Correlation Matrix] [paper deel 3 kend...] [2011-12-23 00:00:38] [d5821fed422662f85834b1edae505ce2]
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Dataseries X:
158258	48	18	20465
186930	53	20	33629
7215	0	0	1423
128162	51	27	25629
226974	76	31	54002
500344	125	36	151036
171007	59	23	33287
179835	80	30	31172
154581	55	30	28113
278960	67	26	57803
121844	50	24	49830
183086	77	30	52143
98796	44	22	21055
209322	79	25	47007
157125	51	18	28735
154565	54	22	59147
134198	75	33	78950
75548	4	15	13497
150680	73	34	46154
27997	13	18	53249
69919	19	15	10726
233044	93	30	83700
195820	38	25	40400
127994	48	34	33797
145433	50	21	36205
170864	48	21	30165
199655	60	25	58534
188633	81	31	44663
354266	60	31	92556
192399	52	20	40078
165753	50	28	34711
173721	60	20	31076
126739	53	17	74608
224762	76	25	58092
219428	63	24	42009
0	0	0	0
217267	54	27	36022
99706	44	14	23333
136733	36	35	53349
249965	83	34	92596
232951	105	22	49598
143755	37	34	44093
95734	25	23	84205
191416	63	24	63369
114820	55	26	60132
157721	41	22	37403
81293	23	35	24460
216281	67	24	46456
223771	54	31	66616
160344	68	26	41554
48188	12	22	22346
145235	84	21	30874
287839	66	27	68701
235223	56	30	35728
195583	67	33	29010
145942	40	11	23110
207309	53	26	38844
93764	26	26	27084
151985	67	23	35139
190545	36	38	57476
146414	50	30	33277
130794	48	19	31141
124234	46	19	61281
112718	53	26	25820
160817	27	26	23284
99070	38	33	35378
178653	68	36	74990
138708	93	25	29653
114408	59	24	64622
31970	5	21	4157
224494	53	19	29245
123328	36	12	50008
113504	72	30	52338
105932	49	21	13310
162203	81	34	92901
100098	27	32	10956
174768	94	28	34241
156908	71	28	75043
77269	18	21	21152
84971	34	31	42249
80522	54	26	42005
276525	44	29	41152
62974	26	23	14399
120296	44	25	28263
75555	35	22	17215
157988	32	26	48140
224562	55	33	62897
115019	58	24	22883
99602	44	24	41622
151804	39	21	40715
146005	49	28	65897
163444	72	27	76542
151517	39	25	37477
133686	28	15	53216
58128	24	13	40911
234325	49	36	57021
195576	96	24	73116
19349	13	1	3895
213189	32	24	46609
151672	41	31	29351
59117	24	4	2325
71931	52	20	31747
126653	57	23	32665
113552	28	23	19249
85338	36	12	15292
27676	2	16	5842
138522	80	29	33994
122417	29	26	13018
0	0	0	0
87592	46	25	98177
107205	25	21	37941
144664	51	23	31032
136540	59	21	32683
73645	36	21	34545
3616	0	0	0
0	0	0	0
175055	38	23	27525
144618	68	33	66856
152826	28	28	28549
113245	36	23	38610
43410	7	1	2781
175762	70	29	41211
93634	30	17	22698
117426	59	31	41194
60493	3	12	32689
19764	10	2	5752
164062	46	21	26757
128144	34	26	22527
154959	54	29	44810
11796	1	2	0
10674	0	0	0
138547	35	18	100674
6836	0	1	0
154135	48	21	57786
5118	5	0	0
40248	8	4	5444
0	0	0	0
120460	36	25	28470
88837	21	26	61849
7131	0	0	0
9056	0	4	2179
68916	15	17	8019
132697	50	21	39644
100681	17	22	23494




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=158314&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=158314&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158314&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=pearson)
TimeBlogsPeerreviewCharacters
Time10.7760.6770.691
Blogs0.77610.6750.661
Peerreview0.6770.67510.619
Characters0.6910.6610.6191

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Time & Blogs & Peerreview & Characters \tabularnewline
Time & 1 & 0.776 & 0.677 & 0.691 \tabularnewline
Blogs & 0.776 & 1 & 0.675 & 0.661 \tabularnewline
Peerreview & 0.677 & 0.675 & 1 & 0.619 \tabularnewline
Characters & 0.691 & 0.661 & 0.619 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158314&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Time[/C][C]Blogs[/C][C]Peerreview[/C][C]Characters[/C][/ROW]
[ROW][C]Time[/C][C]1[/C][C]0.776[/C][C]0.677[/C][C]0.691[/C][/ROW]
[ROW][C]Blogs[/C][C]0.776[/C][C]1[/C][C]0.675[/C][C]0.661[/C][/ROW]
[ROW][C]Peerreview[/C][C]0.677[/C][C]0.675[/C][C]1[/C][C]0.619[/C][/ROW]
[ROW][C]Characters[/C][C]0.691[/C][C]0.661[/C][C]0.619[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158314&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158314&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)
TimeBlogsPeerreviewCharacters
Time10.7760.6770.691
Blogs0.77610.6750.661
Peerreview0.6770.67510.619
Characters0.6910.6610.6191







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Time;Blogs0.77650.75360.5772
p-value(0)(0)(0)
Time;Peerreview0.67740.58690.4368
p-value(0)(0)(0)
Time;Characters0.69060.62060.4673
p-value(0)(0)(0)
Blogs;Peerreview0.67510.58980.4394
p-value(0)(0)(0)
Blogs;Characters0.66110.63610.4757
p-value(0)(0)(0)
Peerreview;Characters0.61930.57280.4286
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
Time;Blogs & 0.7765 & 0.7536 & 0.5772 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;Peerreview & 0.6774 & 0.5869 & 0.4368 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;Characters & 0.6906 & 0.6206 & 0.4673 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Blogs;Peerreview & 0.6751 & 0.5898 & 0.4394 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Blogs;Characters & 0.6611 & 0.6361 & 0.4757 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Peerreview;Characters & 0.6193 & 0.5728 & 0.4286 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158314&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]Time;Blogs[/C][C]0.7765[/C][C]0.7536[/C][C]0.5772[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;Peerreview[/C][C]0.6774[/C][C]0.5869[/C][C]0.4368[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;Characters[/C][C]0.6906[/C][C]0.6206[/C][C]0.4673[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Blogs;Peerreview[/C][C]0.6751[/C][C]0.5898[/C][C]0.4394[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Blogs;Characters[/C][C]0.6611[/C][C]0.6361[/C][C]0.4757[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Peerreview;Characters[/C][C]0.6193[/C][C]0.5728[/C][C]0.4286[/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=158314&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158314&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
Time;Blogs0.77650.75360.5772
p-value(0)(0)(0)
Time;Peerreview0.67740.58690.4368
p-value(0)(0)(0)
Time;Characters0.69060.62060.4673
p-value(0)(0)(0)
Blogs;Peerreview0.67510.58980.4394
p-value(0)(0)(0)
Blogs;Characters0.66110.63610.4757
p-value(0)(0)(0)
Peerreview;Characters0.61930.57280.4286
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')