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*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

Tue, 13 Dec 2011 04:41:37 -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/13/t1323769319mxdj773bkv0rnft.htm/, Retrieved Thu, 02 May 2024 17:39:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154318, Retrieved Thu, 02 May 2024 17:39:34 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

131

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

-     [Kendall tau Correlation Matrix] [] [2010-12-05 18:04:16] [b98453cac15ba1066b407e146608df68]
- RMPD    [Kendall tau Correlation Matrix] [Kendall's tau Cor...] [2011-12-13 09:41:37] [080b56dea5ee02335c893a05354948d0] [Current]

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Dataseries X:

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Boxplots

210907	3	79	30	94	0
120982	4	58	28	103	0
176508	12	60	38	93	1
385534	0	121	25	91	0
149061	5	43	26	93	0
165446	0	69	25	60	1
237213	0	78	38	123	1
133131	7	44	30	90	1
324799	0	158	47	168	1
230964	4	102	30	115	0
236785	3	77	31	71	1
135473	0	82	23	66	0
215147	0	101	36	117	0
344297	1	80	30	108	1
153935	5	50	25	84	0
174724	0	123	34	120	1
174415	0	73	31	114	1
225548	5	81	31	94	0
223632	0	105	33	120	1
124817	0	47	25	81	1
210767	3	94	35	133	0
170266	4	44	42	122	0
294424	2	107	33	124	0
325107	0	84	36	126	1
7176	0	0	0	0	1
106408	1	33	14	37	0
96560	0	42	17	38	0
265769	2	96	32	120	1
149112	6	56	35	95	0
175824	0	57	20	77	1
152871	5	59	28	90	0
111665	4	39	28	80	1
362301	2	76	34	110	1
183167	0	91	39	138	0
168809	0	76	28	100	1
24188	0	8	4	7	1
329267	8	79	39	140	1
218946	1	76	29	96	1
244052	5	101	44	164	1
341570	1	94	21	78	1
103597	1	27	16	49	0
256462	0	123	35	124	1
235800	8	105	23	62	0
196553	2	41	29	99	1
174184	0	72	25	70	1
143246	5	67	27	104	0
187559	8	75	36	116	1
187681	2	114	28	91	0
73566	6	22	23	67	1
167488	2	69	28	72	0
143756	0	105	34	120	0
243199	3	88	28	105	0
182999	6	73	34	104	1
152299	0	62	33	98	1
346485	0	118	38	111	1
193339	2	100	35	71	1
122774	0	24	24	69	1
130585	5	67	29	107	0
112611	0	46	20	73	1
286468	1	57	29	107	1
148446	1	135	37	129	1
182079	2	124	33	118	0
140344	6	33	25	73	1
220516	1	98	32	119	1
243060	4	58	29	104	1
162765	2	68	28	107	1
232138	0	131	31	90	1
265318	10	110	52	197	0
85574	0	37	21	36	1
310839	9	130	24	85	0
225060	7	93	41	139	0
232317	0	118	33	106	1
144966	0	39	32	50	0
164709	0	81	31	63	1
220801	1	51	18	63	1
99466	0	28	23	69	0
92661	1	40	17	41	1
133328	0	56	20	56	1
61361	0	27	12	25	1
100750	0	83	30	93	1
102010	3	28	13	44	0
101523	0	59	22	87	1
243511	0	133	42	110	1
22938	0	12	1	0	1
152474	0	106	32	83	1
99923	0	44	25	80	0
132487	0	71	36	98	1
317394	1	116	31	82	0
21054	0	4	0	0	1
209641	5	62	24	60	1
22648	0	12	13	28	0
31414	0	18	8	9	0
46698	0	14	13	33	1
131698	0	60	19	59	1
244749	2	98	33	115	1
128423	8	32	38	120	0
97839	2	25	24	66	0
272458	0	100	43	152	1
108043	1	45	14	38	1
328107	3	129	41	144	0
351067	3	136	45	160	1
158015	0	59	31	114	0
229242	4	63	31	119	1
84207	11	14	30	101	1
120445	0	36	16	56	0
324598	0	113	37	133	0
131069	4	47	30	83	0
204271	0	92	35	116	0
116048	0	50	20	50	0
250047	0	41	18	61	1
299775	9	91	31	97	1
195838	1	111	31	98	0
173260	3	41	21	78	1
254488	10	120	39	117	0
92499	0	25	18	55	1
224330	1	131	39	132	0
135781	2	45	14	44	0
74408	4	29	7	21	1
81240	0	58	17	50	0
181633	2	47	30	73	1
271856	1	109	37	86	1
95227	0	37	32	48	1
98146	0	15	17	48	0
59194	6	7	24	68	0
139942	0	54	22	87	1
118612	2	54	12	43	0
72880	0	14	19	67	1
65475	2	16	13	46	1
71965	1	32	15	56	1
135131	0	38	15	60	0
108446	1	22	17	65	0
181528	0	32	16	60	1
134019	0	32	18	54	1
121848	0	37	17	52	0
81872	0	32	16	61	0
58981	7	0	23	61	0
53515	2	5	22	81	0
56375	7	10	13	40	1
65490	3	27	16	40	1
76302	0	29	20	68	1
104011	6	25	22	79	1
98104	2	55	17	47	0
30989	0	5	17	41	1
135458	3	43	12	29	0
63123	1	34	17	60	1
74914	0	35	23	79	1
31774	1	0	17	47	0
81437	0	37	14	40	1
65745	0	26	21	42	1
56653	0	38	18	49	1
158399	0	23	18	57	1
73624	0	30	17	40	1
91899	0	18	15	33	1
139526	0	28	21	77	1
51567	2	21	14	45	0
102538	1	50	15	45	0
86678	0	12	15	50	1
150580	0	27	22	71	1
99611	0	41	21	67	1
99373	1	12	18	62	0
86230	0	21	17	54	0
30837	0	8	4	4	0
31706	0	26	10	25	1
89806	0	27	16	40	1
64175	0	37	18	59	0
59382	0	29	12	24	0
119308	0	32	16	58	0
76702	0	35	21	42	0
19764	1	10	2	4	1
84105	0	17	17	63	0
64187	0	10	16	54	1
72535	0	17	16	39	1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154318&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154318&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154318&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	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Correlations for all pairs of data series (method=kendall)
	time_in_rfc	shared_compendiums	blogged_computations	compendiums_reviewed	feedback_messages_p120	What_is_your_gender?
time_in_rfc	1	0.192	0.665	0.572	0.584	0.026
shared_compendiums	0.192	1	0.122	0.197	0.225	-0.173
blogged_computations	0.665	0.122	1	0.582	0.559	-0.029
compendiums_reviewed	0.572	0.197	0.582	1	0.773	0.018
feedback_messages_p120	0.584	0.225	0.559	0.773	1	-0.017
What_is_your_gender?	0.026	-0.173	-0.029	0.018	-0.017	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & time_in_rfc & shared_compendiums & blogged_computations & compendiums_reviewed & feedback_messages_p120 & What_is_your_gender? \tabularnewline
time_in_rfc & 1 & 0.192 & 0.665 & 0.572 & 0.584 & 0.026 \tabularnewline
shared_compendiums & 0.192 & 1 & 0.122 & 0.197 & 0.225 & -0.173 \tabularnewline
blogged_computations & 0.665 & 0.122 & 1 & 0.582 & 0.559 & -0.029 \tabularnewline
compendiums_reviewed & 0.572 & 0.197 & 0.582 & 1 & 0.773 & 0.018 \tabularnewline
feedback_messages_p120 & 0.584 & 0.225 & 0.559 & 0.773 & 1 & -0.017 \tabularnewline
What_is_your_gender? & 0.026 & -0.173 & -0.029 & 0.018 & -0.017 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154318&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]time_in_rfc[/C][C]shared_compendiums[/C][C]blogged_computations[/C][C]compendiums_reviewed[/C][C]feedback_messages_p120[/C][C]What_is_your_gender?[/C][/ROW]
[ROW][C]time_in_rfc[/C][C]1[/C][C]0.192[/C][C]0.665[/C][C]0.572[/C][C]0.584[/C][C]0.026[/C][/ROW]
[ROW][C]shared_compendiums[/C][C]0.192[/C][C]1[/C][C]0.122[/C][C]0.197[/C][C]0.225[/C][C]-0.173[/C][/ROW]
[ROW][C]blogged_computations[/C][C]0.665[/C][C]0.122[/C][C]1[/C][C]0.582[/C][C]0.559[/C][C]-0.029[/C][/ROW]
[ROW][C]compendiums_reviewed[/C][C]0.572[/C][C]0.197[/C][C]0.582[/C][C]1[/C][C]0.773[/C][C]0.018[/C][/ROW]
[ROW][C]feedback_messages_p120[/C][C]0.584[/C][C]0.225[/C][C]0.559[/C][C]0.773[/C][C]1[/C][C]-0.017[/C][/ROW]
[ROW][C]What_is_your_gender?[/C][C]0.026[/C][C]-0.173[/C][C]-0.029[/C][C]0.018[/C][C]-0.017[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154318&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154318&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)
	time_in_rfc	shared_compendiums	blogged_computations	compendiums_reviewed	feedback_messages_p120	What_is_your_gender?
time_in_rfc	1	0.192	0.665	0.572	0.584	0.026
shared_compendiums	0.192	1	0.122	0.197	0.225	-0.173
blogged_computations	0.665	0.122	1	0.582	0.559	-0.029
compendiums_reviewed	0.572	0.197	0.582	1	0.773	0.018
feedback_messages_p120	0.584	0.225	0.559	0.773	1	-0.017
What_is_your_gender?	0.026	-0.173	-0.029	0.018	-0.017	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
time_in_rfc;shared_compendiums	0.208	0.2626	0.1916
p-value	(0.0062)	(5e-04)	(7e-04)
time_in_rfc;blogged_computations	0.8164	0.8561	0.6654
p-value	(0)	(0)	(0)
time_in_rfc;compendiums_reviewed	0.7282	0.7641	0.5715
p-value	(0)	(0)	(0)
time_in_rfc;feedback_messages_p120	0.7469	0.7812	0.5842
p-value	(0)	(0)	(0)
time_in_rfc;What_is_your_gender?	0.0426	0.032	0.0262
p-value	(0.5793)	(0.6765)	(0.6752)
shared_compendiums;blogged_computations	0.114	0.1638	0.1218
p-value	(0.1366)	(0.0318)	(0.032)
shared_compendiums;compendiums_reviewed	0.3322	0.2779	0.1975
p-value	(0)	(2e-04)	(6e-04)
shared_compendiums;feedback_messages_p120	0.3203	0.3072	0.225
p-value	(0)	(0)	(1e-04)
shared_compendiums;What_is_your_gender?	-0.1384	-0.1912	-0.1727
p-value	(0.0703)	(0.012)	(0.0124)
blogged_computations;compendiums_reviewed	0.7636	0.7737	0.582
p-value	(0)	(0)	(0)
blogged_computations;feedback_messages_p120	0.754	0.7566	0.5587
p-value	(0)	(0)	(0)
blogged_computations;What_is_your_gender?	-0.0343	-0.0351	-0.0289
p-value	(0.6553)	(0.6473)	(0.6459)
compendiums_reviewed;feedback_messages_p120	0.9268	0.9118	0.7727
p-value	(0)	(0)	(0)
compendiums_reviewed;What_is_your_gender?	-0.0077	0.0213	0.0177
p-value	(0.9201)	(0.7819)	(0.781)
feedback_messages_p120;What_is_your_gender?	-0.0323	-0.0209	-0.0172
p-value	(0.6742)	(0.7856)	(0.7847)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
time_in_rfc;shared_compendiums & 0.208 & 0.2626 & 0.1916 \tabularnewline
p-value & (0.0062) & (5e-04) & (7e-04) \tabularnewline
time_in_rfc;blogged_computations & 0.8164 & 0.8561 & 0.6654 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;compendiums_reviewed & 0.7282 & 0.7641 & 0.5715 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;feedback_messages_p120 & 0.7469 & 0.7812 & 0.5842 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;What_is_your_gender? & 0.0426 & 0.032 & 0.0262 \tabularnewline
p-value & (0.5793) & (0.6765) & (0.6752) \tabularnewline
shared_compendiums;blogged_computations & 0.114 & 0.1638 & 0.1218 \tabularnewline
p-value & (0.1366) & (0.0318) & (0.032) \tabularnewline
shared_compendiums;compendiums_reviewed & 0.3322 & 0.2779 & 0.1975 \tabularnewline
p-value & (0) & (2e-04) & (6e-04) \tabularnewline
shared_compendiums;feedback_messages_p120 & 0.3203 & 0.3072 & 0.225 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
shared_compendiums;What_is_your_gender? & -0.1384 & -0.1912 & -0.1727 \tabularnewline
p-value & (0.0703) & (0.012) & (0.0124) \tabularnewline
blogged_computations;compendiums_reviewed & 0.7636 & 0.7737 & 0.582 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
blogged_computations;feedback_messages_p120 & 0.754 & 0.7566 & 0.5587 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
blogged_computations;What_is_your_gender? & -0.0343 & -0.0351 & -0.0289 \tabularnewline
p-value & (0.6553) & (0.6473) & (0.6459) \tabularnewline
compendiums_reviewed;feedback_messages_p120 & 0.9268 & 0.9118 & 0.7727 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
compendiums_reviewed;What_is_your_gender? & -0.0077 & 0.0213 & 0.0177 \tabularnewline
p-value & (0.9201) & (0.7819) & (0.781) \tabularnewline
feedback_messages_p120;What_is_your_gender? & -0.0323 & -0.0209 & -0.0172 \tabularnewline
p-value & (0.6742) & (0.7856) & (0.7847) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154318&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_in_rfc;shared_compendiums[/C][C]0.208[/C][C]0.2626[/C][C]0.1916[/C][/ROW]
[ROW][C]p-value[/C][C](0.0062)[/C][C](5e-04)[/C][C](7e-04)[/C][/ROW]
[ROW][C]time_in_rfc;blogged_computations[/C][C]0.8164[/C][C]0.8561[/C][C]0.6654[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time_in_rfc;compendiums_reviewed[/C][C]0.7282[/C][C]0.7641[/C][C]0.5715[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time_in_rfc;feedback_messages_p120[/C][C]0.7469[/C][C]0.7812[/C][C]0.5842[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time_in_rfc;What_is_your_gender?[/C][C]0.0426[/C][C]0.032[/C][C]0.0262[/C][/ROW]
[ROW][C]p-value[/C][C](0.5793)[/C][C](0.6765)[/C][C](0.6752)[/C][/ROW]
[ROW][C]shared_compendiums;blogged_computations[/C][C]0.114[/C][C]0.1638[/C][C]0.1218[/C][/ROW]
[ROW][C]p-value[/C][C](0.1366)[/C][C](0.0318)[/C][C](0.032)[/C][/ROW]
[ROW][C]shared_compendiums;compendiums_reviewed[/C][C]0.3322[/C][C]0.2779[/C][C]0.1975[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](2e-04)[/C][C](6e-04)[/C][/ROW]
[ROW][C]shared_compendiums;feedback_messages_p120[/C][C]0.3203[/C][C]0.3072[/C][C]0.225[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]shared_compendiums;What_is_your_gender?[/C][C]-0.1384[/C][C]-0.1912[/C][C]-0.1727[/C][/ROW]
[ROW][C]p-value[/C][C](0.0703)[/C][C](0.012)[/C][C](0.0124)[/C][/ROW]
[ROW][C]blogged_computations;compendiums_reviewed[/C][C]0.7636[/C][C]0.7737[/C][C]0.582[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]blogged_computations;feedback_messages_p120[/C][C]0.754[/C][C]0.7566[/C][C]0.5587[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]blogged_computations;What_is_your_gender?[/C][C]-0.0343[/C][C]-0.0351[/C][C]-0.0289[/C][/ROW]
[ROW][C]p-value[/C][C](0.6553)[/C][C](0.6473)[/C][C](0.6459)[/C][/ROW]
[ROW][C]compendiums_reviewed;feedback_messages_p120[/C][C]0.9268[/C][C]0.9118[/C][C]0.7727[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]compendiums_reviewed;What_is_your_gender?[/C][C]-0.0077[/C][C]0.0213[/C][C]0.0177[/C][/ROW]
[ROW][C]p-value[/C][C](0.9201)[/C][C](0.7819)[/C][C](0.781)[/C][/ROW]
[ROW][C]feedback_messages_p120;What_is_your_gender?[/C][C]-0.0323[/C][C]-0.0209[/C][C]-0.0172[/C][/ROW]
[ROW][C]p-value[/C][C](0.6742)[/C][C](0.7856)[/C][C](0.7847)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154318&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154318&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
time_in_rfc;shared_compendiums	0.208	0.2626	0.1916
p-value	(0.0062)	(5e-04)	(7e-04)
time_in_rfc;blogged_computations	0.8164	0.8561	0.6654
p-value	(0)	(0)	(0)
time_in_rfc;compendiums_reviewed	0.7282	0.7641	0.5715
p-value	(0)	(0)	(0)
time_in_rfc;feedback_messages_p120	0.7469	0.7812	0.5842
p-value	(0)	(0)	(0)
time_in_rfc;What_is_your_gender?	0.0426	0.032	0.0262
p-value	(0.5793)	(0.6765)	(0.6752)
shared_compendiums;blogged_computations	0.114	0.1638	0.1218
p-value	(0.1366)	(0.0318)	(0.032)
shared_compendiums;compendiums_reviewed	0.3322	0.2779	0.1975
p-value	(0)	(2e-04)	(6e-04)
shared_compendiums;feedback_messages_p120	0.3203	0.3072	0.225
p-value	(0)	(0)	(1e-04)
shared_compendiums;What_is_your_gender?	-0.1384	-0.1912	-0.1727
p-value	(0.0703)	(0.012)	(0.0124)
blogged_computations;compendiums_reviewed	0.7636	0.7737	0.582
p-value	(0)	(0)	(0)
blogged_computations;feedback_messages_p120	0.754	0.7566	0.5587
p-value	(0)	(0)	(0)
blogged_computations;What_is_your_gender?	-0.0343	-0.0351	-0.0289
p-value	(0.6553)	(0.6473)	(0.6459)
compendiums_reviewed;feedback_messages_p120	0.9268	0.9118	0.7727
p-value	(0)	(0)	(0)
compendiums_reviewed;What_is_your_gender?	-0.0077	0.0213	0.0177
p-value	(0.9201)	(0.7819)	(0.781)
feedback_messages_p120;What_is_your_gender?	-0.0323	-0.0209	-0.0172
p-value	(0.6742)	(0.7856)	(0.7847)

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code