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Author

*The author of this computation has been verified*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Thu, 22 Dec 2011 12:18:04 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/22/t1324574330qm6zmoxi9nzqi4j.htm/, Retrieved Fri, 03 May 2024 08:00:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159753, Retrieved Fri, 03 May 2024 08:00:40 +0000

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No (this computation is public)

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Kendall tau Correlation Matrix] [rfc pearson] [2011-12-21 09:41:55] [26f9350dcf28f408b6e37deed68b781e]
-    D    [Kendall tau Correlation Matrix] [] [2011-12-22 17:18:04] [0b5336524434486374423216ee0ff518] [Current]

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95	20465	115	48	21	23975
63	33629	76	58	20	85634
18	1423	1	0	0	1929
97	25629	155	67	27	36294
139	54002	125	83	31	72255
271	151036	278	137	36	189748
60	33287	93	65	26	61834
60	31172	59	86	30	68167
45	28113	87	62	30	38462
100	57803	130	72	27	101219
76	49830	158	50	24	43270
72	52143	120	88	30	76183
109	21055	87	62	22	31476
120	47007	264	79	28	62157
67	28735	51	56	18	46261
89	59147	85	54	22	50063
59	78950	100	81	37	64483
61	13497	72	13	15	2341
89	46154	147	80	34	48149
29	53249	49	19	18	12743
63	10726	40	32	15	18743
103	83700	99	99	30	97057
75	40400	127	38	25	17675
58	33797	165	59	34	33106
89	36205	41	54	21	53311
34	30165	160	63	21	42754
168	58534	92	66	25	59056
96	44663	59	90	31	101621
122	92556	89	75	31	118120
46	40078	90	61	20	79572
45	34711	76	61	28	42744
48	31076	116	63	22	65931
107	74608	92	53	17	38575
133	58092	362	135	25	28795
56	42009	85	73	25	94440
1	0	0	0	0	0
65	36022	63	54	31	38229
54	23333	138	54	14	31972
52	53349	270	46	35	40071
68	92596	64	83	34	132480
72	49598	96	106	22	62797
61	44093	62	44	34	40429
33	84205	35	27	23	45545
81	63369	66	73	24	57568
51	60132	56	71	26	39019
100	37403	41	44	23	53866
33	24460	49	23	35	38345
106	46456	121	78	24	50210
90	66616	113	60	31	80947
60	41554	190	73	30	43461
28	22346	37	12	22	14812
71	30874	52	104	23	37819
78	68701	89	95	27	102738
80	35728	73	57	30	54509
60	29010	49	67	33	62956
57	23110	77	44	12	55411
71	38844	58	53	26	50611
26	27084	75	26	26	26692
68	35139	32	67	23	60056
101	57476	59	36	38	25155
66	33277	71	56	32	42840
84	31141	91	52	21	39358
64	61281	87	54	22	47241
40	25820	48	61	26	49611
39	23284	63	27	28	41833
43	35378	41	58	33	48930
72	74990	86	76	36	110600
66	29653	152	93	25	52235
40	64622	49	59	25	53986
15	4157	40	5	21	4105
116	29245	135	58	19	59331
79	50008	83	42	12	47796
68	52338	62	88	30	38302
73	13310	91	53	21	14063
71	92901	95	81	39	54414
45	10956	82	35	32	9903
60	34241	112	102	28	53987
98	75043	70	71	29	88937
41	21152	78	28	21	21928
72	42249	105	34	31	29487
76	42005	49	54	26	35334
65	41152	60	49	29	57596
30	14399	49	30	23	29750
41	28263	132	57	25	41029
48	17215	49	54	22	12416
59	48140	71	38	26	51158
239	62897	102	63	33	79935
115	22883	74	58	24	26552
66	41622	49	49	24	25807
54	40715	74	46	21	50620
42	65897	59	51	28	61467
84	76542	91	90	28	65292
58	37477	68	39	25	55516
61	53216	81	28	15	42006
43	40911	33	26	13	26273
119	57021	166	52	36	90248
71	73116	97	96	27	61476
12	3895	15	13	1	9604
109	46609	105	43	24	45108
86	29351	61	42	31	47232
30	2325	11	30	4	3439
26	31747	45	59	21	30553
57	32665	89	73	27	24751
68	19249	72	40	26	34458
42	15292	27	36	12	24649
22	5842	59	2	16	2342
52	33994	127	103	29	52739
38	13018	48	30	26	6245
0	0	0	0	0	0
34	98177	58	46	25	35381
68	37941	57	25	21	19595
46	31032	60	59	24	50848
66	32683	77	60	21	39443
63	34545	71	36	21	27023
5	0	5	0	0	0
0	0	0	0	0	0
45	27525	70	45	23	61022
96	66856	76	79	33	63528
102	28549	124	30	32	34835
40	38610	56	43	23	37172
19	2781	63	7	1	13
75	41211	92	80	29	62548
45	22698	58	32	20	31334
60	41194	64	84	33	20839
40	32689	29	3	12	5084
12	5752	19	10	2	9927
56	26757	64	47	21	53229
35	22527	79	35	28	29877
54	44810	104	54	35	37310
9	0	22	1	2	0
9	0	7	0	0	0
59	100674	37	46	18	50067
3	0	5	0	1	0
68	57786	48	51	21	47708
3	0	1	5	0	0
16	5444	34	8	4	6012
0	0	0	0	0	0
51	28470	53	38	29	27749
38	61849	44	21	26	47555
4	0	0	0	0	0
15	2179	18	0	4	1336
29	8019	52	18	19	11017
54	39644	56	53	22	55184
20	23494	50	17	22	43485

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=159753&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=159753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159753&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Correlations for all pairs of data series (method=pearson)
	#Logins	#Characters(compendium)	#CompendiumViews(PR)	#BloggedComputations	#ReviewedCompendiums	#TimeSpent(compendium)
#Logins	1	0.617	0.597	0.642	0.549	0.65
#Characters(compendium)	0.617	1	0.429	0.639	0.614	0.756
#CompendiumViews(PR)	0.597	0.429	1	0.62	0.511	0.434
#BloggedComputations	0.642	0.639	0.62	1	0.67	0.725
#ReviewedCompendiums	0.549	0.614	0.511	0.67	1	0.609
#TimeSpent(compendium)	0.65	0.756	0.434	0.725	0.609	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & #Logins & #Characters(compendium) & #CompendiumViews(PR) & #BloggedComputations & #ReviewedCompendiums & #TimeSpent(compendium) \tabularnewline
#Logins & 1 & 0.617 & 0.597 & 0.642 & 0.549 & 0.65 \tabularnewline
#Characters(compendium) & 0.617 & 1 & 0.429 & 0.639 & 0.614 & 0.756 \tabularnewline
#CompendiumViews(PR) & 0.597 & 0.429 & 1 & 0.62 & 0.511 & 0.434 \tabularnewline
#BloggedComputations & 0.642 & 0.639 & 0.62 & 1 & 0.67 & 0.725 \tabularnewline
#ReviewedCompendiums & 0.549 & 0.614 & 0.511 & 0.67 & 1 & 0.609 \tabularnewline
#TimeSpent(compendium) & 0.65 & 0.756 & 0.434 & 0.725 & 0.609 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159753&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]#Logins[/C][C]#Characters(compendium)[/C][C]#CompendiumViews(PR)[/C][C]#BloggedComputations[/C][C]#ReviewedCompendiums[/C][C]#TimeSpent(compendium)[/C][/ROW]
[ROW][C]#Logins[/C][C]1[/C][C]0.617[/C][C]0.597[/C][C]0.642[/C][C]0.549[/C][C]0.65[/C][/ROW]
[ROW][C]#Characters(compendium)[/C][C]0.617[/C][C]1[/C][C]0.429[/C][C]0.639[/C][C]0.614[/C][C]0.756[/C][/ROW]
[ROW][C]#CompendiumViews(PR)[/C][C]0.597[/C][C]0.429[/C][C]1[/C][C]0.62[/C][C]0.511[/C][C]0.434[/C][/ROW]
[ROW][C]#BloggedComputations[/C][C]0.642[/C][C]0.639[/C][C]0.62[/C][C]1[/C][C]0.67[/C][C]0.725[/C][/ROW]
[ROW][C]#ReviewedCompendiums[/C][C]0.549[/C][C]0.614[/C][C]0.511[/C][C]0.67[/C][C]1[/C][C]0.609[/C][/ROW]
[ROW][C]#TimeSpent(compendium)[/C][C]0.65[/C][C]0.756[/C][C]0.434[/C][C]0.725[/C][C]0.609[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159753&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)
	#Logins	#Characters(compendium)	#CompendiumViews(PR)	#BloggedComputations	#ReviewedCompendiums	#TimeSpent(compendium)
#Logins	1	0.617	0.597	0.642	0.549	0.65
#Characters(compendium)	0.617	1	0.429	0.639	0.614	0.756
#CompendiumViews(PR)	0.597	0.429	1	0.62	0.511	0.434
#BloggedComputations	0.642	0.639	0.62	1	0.67	0.725
#ReviewedCompendiums	0.549	0.614	0.511	0.67	1	0.609
#TimeSpent(compendium)	0.65	0.756	0.434	0.725	0.609	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
#Logins;#Characters(compendium)	0.6167	0.601	0.4561
p-value	(0)	(0)	(0)
#Logins;#CompendiumViews(PR)	0.5974	0.6332	0.4714
p-value	(0)	(0)	(0)
#Logins;#BloggedComputations	0.6417	0.639	0.4779
p-value	(0)	(0)	(0)
#Logins;#ReviewedCompendiums	0.5486	0.4845	0.3573
p-value	(0)	(0)	(0)
#Logins;#TimeSpent(compendium)	0.65	0.5869	0.4332
p-value	(0)	(0)	(0)
#Characters(compendium);#CompendiumViews(PR)	0.4294	0.4504	0.3186
p-value	(0)	(0)	(0)
#Characters(compendium);#BloggedComputations	0.6386	0.6027	0.4423
p-value	(0)	(0)	(0)
#Characters(compendium);#ReviewedCompendiums	0.6138	0.561	0.4205
p-value	(0)	(0)	(0)
#Characters(compendium);#TimeSpent(compendium)	0.7563	0.7017	0.5394
p-value	(0)	(0)	(0)
#CompendiumViews(PR);#BloggedComputations	0.6197	0.6208	0.4549
p-value	(0)	(0)	(0)
#CompendiumViews(PR);#ReviewedCompendiums	0.5105	0.5086	0.376
p-value	(0)	(0)	(0)
#CompendiumViews(PR);#TimeSpent(compendium)	0.434	0.5013	0.3558
p-value	(0)	(0)	(0)
#BloggedComputations;#ReviewedCompendiums	0.6697	0.594	0.4392
p-value	(0)	(0)	(0)
#BloggedComputations;#TimeSpent(compendium)	0.725	0.7357	0.5618
p-value	(0)	(0)	(0)
#ReviewedCompendiums;#TimeSpent(compendium)	0.6093	0.5483	0.4088
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
#Logins;#Characters(compendium) & 0.6167 & 0.601 & 0.4561 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Logins;#CompendiumViews(PR) & 0.5974 & 0.6332 & 0.4714 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Logins;#BloggedComputations & 0.6417 & 0.639 & 0.4779 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Logins;#ReviewedCompendiums & 0.5486 & 0.4845 & 0.3573 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Logins;#TimeSpent(compendium) & 0.65 & 0.5869 & 0.4332 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Characters(compendium);#CompendiumViews(PR) & 0.4294 & 0.4504 & 0.3186 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Characters(compendium);#BloggedComputations & 0.6386 & 0.6027 & 0.4423 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Characters(compendium);#ReviewedCompendiums & 0.6138 & 0.561 & 0.4205 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Characters(compendium);#TimeSpent(compendium) & 0.7563 & 0.7017 & 0.5394 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#CompendiumViews(PR);#BloggedComputations & 0.6197 & 0.6208 & 0.4549 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#CompendiumViews(PR);#ReviewedCompendiums & 0.5105 & 0.5086 & 0.376 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#CompendiumViews(PR);#TimeSpent(compendium) & 0.434 & 0.5013 & 0.3558 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#BloggedComputations;#ReviewedCompendiums & 0.6697 & 0.594 & 0.4392 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#BloggedComputations;#TimeSpent(compendium) & 0.725 & 0.7357 & 0.5618 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#ReviewedCompendiums;#TimeSpent(compendium) & 0.6093 & 0.5483 & 0.4088 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159753&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]#Logins;#Characters(compendium)[/C][C]0.6167[/C][C]0.601[/C][C]0.4561[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Logins;#CompendiumViews(PR)[/C][C]0.5974[/C][C]0.6332[/C][C]0.4714[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Logins;#BloggedComputations[/C][C]0.6417[/C][C]0.639[/C][C]0.4779[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Logins;#ReviewedCompendiums[/C][C]0.5486[/C][C]0.4845[/C][C]0.3573[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Logins;#TimeSpent(compendium)[/C][C]0.65[/C][C]0.5869[/C][C]0.4332[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Characters(compendium);#CompendiumViews(PR)[/C][C]0.4294[/C][C]0.4504[/C][C]0.3186[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Characters(compendium);#BloggedComputations[/C][C]0.6386[/C][C]0.6027[/C][C]0.4423[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Characters(compendium);#ReviewedCompendiums[/C][C]0.6138[/C][C]0.561[/C][C]0.4205[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Characters(compendium);#TimeSpent(compendium)[/C][C]0.7563[/C][C]0.7017[/C][C]0.5394[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#CompendiumViews(PR);#BloggedComputations[/C][C]0.6197[/C][C]0.6208[/C][C]0.4549[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#CompendiumViews(PR);#ReviewedCompendiums[/C][C]0.5105[/C][C]0.5086[/C][C]0.376[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#CompendiumViews(PR);#TimeSpent(compendium)[/C][C]0.434[/C][C]0.5013[/C][C]0.3558[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#BloggedComputations;#ReviewedCompendiums[/C][C]0.6697[/C][C]0.594[/C][C]0.4392[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#BloggedComputations;#TimeSpent(compendium)[/C][C]0.725[/C][C]0.7357[/C][C]0.5618[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#ReviewedCompendiums;#TimeSpent(compendium)[/C][C]0.6093[/C][C]0.5483[/C][C]0.4088[/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=159753&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159753&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
pair	Pearson r	Spearman rho	Kendall tau
#Logins;#Characters(compendium)	0.6167	0.601	0.4561
p-value	(0)	(0)	(0)
#Logins;#CompendiumViews(PR)	0.5974	0.6332	0.4714
p-value	(0)	(0)	(0)
#Logins;#BloggedComputations	0.6417	0.639	0.4779
p-value	(0)	(0)	(0)
#Logins;#ReviewedCompendiums	0.5486	0.4845	0.3573
p-value	(0)	(0)	(0)
#Logins;#TimeSpent(compendium)	0.65	0.5869	0.4332
p-value	(0)	(0)	(0)
#Characters(compendium);#CompendiumViews(PR)	0.4294	0.4504	0.3186
p-value	(0)	(0)	(0)
#Characters(compendium);#BloggedComputations	0.6386	0.6027	0.4423
p-value	(0)	(0)	(0)
#Characters(compendium);#ReviewedCompendiums	0.6138	0.561	0.4205
p-value	(0)	(0)	(0)
#Characters(compendium);#TimeSpent(compendium)	0.7563	0.7017	0.5394
p-value	(0)	(0)	(0)
#CompendiumViews(PR);#BloggedComputations	0.6197	0.6208	0.4549
p-value	(0)	(0)	(0)
#CompendiumViews(PR);#ReviewedCompendiums	0.5105	0.5086	0.376
p-value	(0)	(0)	(0)
#CompendiumViews(PR);#TimeSpent(compendium)	0.434	0.5013	0.3558
p-value	(0)	(0)	(0)
#BloggedComputations;#ReviewedCompendiums	0.6697	0.594	0.4392
p-value	(0)	(0)	(0)
#BloggedComputations;#TimeSpent(compendium)	0.725	0.7357	0.5618
p-value	(0)	(0)	(0)
#ReviewedCompendiums;#TimeSpent(compendium)	0.6093	0.5483	0.4088
p-value	(0)	(0)	(0)

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code