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Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 11 Dec 2012 04:14:21 -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/2012/Dec/11/t13552172866xh2a6ysttk2ki4.htm/, Retrieved Thu, 31 Oct 2024 23:15:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198368, Retrieved Thu, 31 Oct 2024 23:15:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167
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 17:44:33] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kendall tau Correlation Matrix] [Pearson Correlati...] [2012-12-06 16:59:12] [37f59b7a972c225c3d32d27fed432050]
-           [Kendall tau Correlation Matrix] [Pearson Correlati...] [2012-12-11 09:14:21] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
210907	56	396	3	30	112285	1
120982	56	297	4	28	84786	1
176508	54	559	12	38	83123	1
179321	89	967	2	30	101193	1
123185	40	270	1	22	38361	1
52746	25	143	3	26	68504	1
385534	92	1562	0	25	119182	1
33170	18	109	0	18	22807	1
101645	63	371	0	11	17140	0
149061	44	656	5	26	116174	1
165446	33	511	0	25	57635	1
237213	84	655	0	38	66198	1
173326	88	465	7	44	71701	1
133131	55	525	7	30	57793	1
258873	60	885	3	40	80444	1
180083	66	497	9	34	53855	1
324799	154	1436	0	47	97668	1
230964	53	612	4	30	133824	1
236785	119	865	3	31	101481	1
135473	41	385	0	23	99645	1
202925	61	567	7	36	114789	1
215147	58	639	0	36	99052	1
344297	75	963	1	30	67654	1
153935	33	398	5	25	65553	1
132943	40	410	7	39	97500	1
174724	92	966	0	34	69112	1
174415	100	801	0	31	82753	1
225548	112	892	5	31	85323	1
223632	73	513	0	33	72654	1
124817	40	469	0	25	30727	1
221698	45	683	0	33	77873	1
210767	60	643	3	35	117478	1
170266	62	535	4	42	74007	1
260561	75	625	1	43	90183	1
84853	31	264	4	30	61542	1
294424	77	992	2	33	101494	1
101011	34	238	0	13	27570	1
215641	46	818	0	32	55813	1
325107	99	937	0	36	79215	1
7176	17	70	0	0	1423	1
167542	66	507	2	28	55461	1
106408	30	260	1	14	31081	1
96560	76	503	0	17	22996	1
265769	146	927	2	32	83122	1
269651	67	1269	10	30	70106	1
149112	56	537	6	35	60578	1
175824	107	910	0	20	39992	1
152871	58	532	5	28	79892	1
111665	34	345	4	28	49810	1
116408	61	918	1	39	71570	1
362301	119	1635	2	34	100708	1
78800	42	330	2	26	33032	1
183167	66	557	0	39	82875	1
277965	89	1178	8	39	139077	1
150629	44	740	3	33	71595	1
168809	66	452	0	28	72260	1
24188	24	218	0	4	5950	1
329267	259	764	8	39	115762	1
65029	17	255	5	18	32551	1
101097	64	454	3	14	31701	1
218946	41	866	1	29	80670	1
244052	68	574	5	44	143558	1
341570	168	1276	1	21	117105	1
103597	43	379	1	16	23789	1
233328	132	825	5	28	120733	1
256462	105	798	0	35	105195	1
206161	71	663	12	28	73107	1
311473	112	1069	8	38	132068	1
235800	94	921	8	23	149193	1
177939	82	858	8	36	46821	1
207176	70	711	8	32	87011	1
196553	57	503	2	29	95260	1
174184	53	382	0	25	55183	1
143246	103	464	5	27	106671	1
187559	121	717	8	36	73511	1
187681	62	690	2	28	92945	1
119016	52	462	5	23	78664	1
182192	52	657	12	40	70054	1
73566	32	385	6	23	22618	1
194979	62	577	7	40	74011	1
167488	45	619	2	28	83737	1
143756	46	479	0	34	69094	1
275541	63	817	4	33	93133	1
243199	75	752	3	28	95536	1
182999	88	430	6	34	225920	1
135649	46	451	2	30	62133	1
152299	53	537	0	33	61370	1
120221	37	519	1	22	43836	1
346485	90	1000	0	38	106117	1
145790	63	637	5	26	38692	1
193339	78	465	2	35	84651	1
80953	25	437	0	8	56622	1
122774	45	711	0	24	15986	1
130585	46	299	5	29	95364	1
112611	41	248	0	20	26706	0
286468	144	1162	1	29	89691	1
241066	82	714	0	45	67267	1
148446	91	905	1	37	126846	1
204713	71	649	1	33	41140	1
182079	63	512	2	33	102860	1
140344	53	472	6	25	51715	1
220516	62	905	1	32	55801	1
243060	63	786	4	29	111813	1
162765	32	489	2	28	120293	1
182613	39	479	3	28	138599	1
232138	62	617	0	31	161647	1
265318	117	925	10	52	115929	1
85574	34	351	0	21	24266	0
310839	92	1144	9	24	162901	1
225060	93	669	7	41	109825	1
232317	54	707	0	33	129838	1
144966	144	458	0	32	37510	1
43287	14	214	4	19	43750	1
155754	61	599	4	20	40652	1
164709	109	572	0	31	87771	1
201940	38	897	0	31	85872	1
235454	73	819	0	32	89275	1
220801	75	720	1	18	44418	0
99466	50	273	0	23	192565	1
92661	61	508	1	17	35232	0
133328	55	506	0	20	40909	0
61361	77	451	0	12	13294	0
125930	75	699	4	17	32387	0
100750	72	407	0	30	140867	1
224549	50	465	4	31	120662	1
82316	32	245	4	10	21233	0
102010	53	370	3	13	44332	0
101523	42	316	0	22	61056	0
243511	71	603	0	42	101338	1
22938	10	154	0	1	1168	1
41566	35	229	5	9	13497	0
152474	65	577	0	32	65567	1
61857	25	192	4	11	25162	1
99923	66	617	0	25	32334	0
132487	41	411	0	36	40735	1
317394	86	975	1	31	91413	1
21054	16	146	0	0	855	1
209641	42	705	5	24	97068	1
22648	19	184	0	13	44339	0
31414	19	200	0	8	14116	1
46698	45	274	0	13	10288	0
131698	65	502	0	19	65622	0
91735	35	382	0	18	16563	0
244749	95	964	2	33	76643	1
184510	49	537	7	40	110681	1
79863	37	438	1	22	29011	0
128423	64	369	8	38	92696	1
97839	38	417	2	24	94785	1
38214	34	276	0	8	8773	1
151101	32	514	2	35	83209	1
272458	65	822	0	43	93815	1
172494	52	389	0	43	86687	1
108043	62	466	1	14	34553	0
328107	65	1255	3	41	105547	1
250579	83	694	0	38	103487	1
351067	95	1024	3	45	213688	1
158015	29	400	0	31	71220	1
98866	18	397	0	13	23517	0
85439	33	350	0	28	56926	1
229242	247	719	4	31	91721	1
351619	139	1277	4	40	115168	1
84207	29	356	11	30	111194	1
120445	118	457	0	16	51009	0
324598	110	1402	0	37	135777	1
131069	67	600	4	30	51513	1
204271	42	480	0	35	74163	1
165543	65	595	1	32	51633	1
141722	94	436	0	27	75345	1
116048	64	230	0	20	33416	0
250047	81	651	0	18	83305	0
299775	95	1367	9	31	98952	1
195838	67	564	1	31	102372	1
173260	63	716	3	21	37238	1
254488	83	747	10	39	103772	1
104389	45	467	5	41	123969	1
136084	30	671	0	13	27142	0
199476	70	861	2	32	135400	1
92499	32	319	0	18	21399	0
224330	83	612	1	39	130115	1
135781	31	433	2	14	24874	0
74408	67	434	4	7	34988	0
81240	66	503	0	17	45549	0
14688	10	85	0	0	6023	1
181633	70	564	2	30	64466	1
271856	103	824	1	37	54990	1
7199	5	74	0	0	1644	1
46660	20	259	0	5	6179	1
17547	5	69	0	1	3926	1
133368	36	535	1	16	32755	0
95227	34	239	0	32	34777	1
152601	48	438	2	24	73224	1
98146	40	459	0	17	27114	0
79619	43	426	3	11	20760	0
59194	31	288	6	24	37636	0
139942	42	498	0	22	65461	0
118612	46	454	2	12	30080	0
72880	33	376	0	19	24094	0
65475	18	225	2	13	69008	0
99643	55	555	1	17	54968	0
71965	35	252	1	15	46090	0
77272	59	208	2	16	27507	0
49289	19	130	1	24	10672	0
135131	66	481	0	15	34029	0
108446	60	389	1	17	46300	0
89746	36	565	3	18	24760	0
44296	25	173	0	20	18779	0
77648	47	278	0	16	21280	0
181528	54	609	0	16	40662	0
134019	53	422	0	18	28987	0
124064	40	445	1	22	22827	0
92630	40	387	4	8	18513	0
121848	39	339	0	17	30594	0
52915	14	181	0	18	24006	0
81872	45	245	0	16	27913	0
58981	36	384	7	23	42744	0
53515	28	212	2	22	12934	0
60812	44	399	0	13	22574	0
56375	30	229	7	13	41385	0
65490	22	224	3	16	18653	0
80949	17	203	0	16	18472	0
76302	31	333	0	20	30976	0
104011	55	384	6	22	63339	0
98104	54	636	2	17	25568	0
67989	21	185	0	18	33747	0
30989	14	93	0	17	4154	0
135458	81	581	3	12	19474	0
73504	35	248	0	7	35130	0
63123	43	304	1	17	39067	0
61254	46	344	1	14	13310	0
74914	30	407	0	23	65892	0
31774	23	170	1	17	4143	0
81437	38	312	0	14	28579	0
87186	54	507	0	15	51776	0
50090	20	224	0	17	21152	0
65745	53	340	0	21	38084	0
56653	45	168	0	18	27717	0
158399	39	443	0	18	32928	0
46455	20	204	0	17	11342	0
73624	24	367	0	17	19499	0
38395	31	210	0	16	16380	0
91899	35	335	0	15	36874	0
139526	151	364	0	21	48259	0
52164	52	178	0	16	16734	0
51567	30	206	2	14	28207	0
70551	31	279	0	15	30143	0
84856	29	387	1	17	41369	0
102538	57	490	1	15	45833	0
86678	40	238	0	15	29156	0
85709	44	343	0	10	35944	0
34662	25	232	0	6	36278	0
150580	77	530	0	22	45588	0
99611	35	291	0	21	45097	0
19349	11	67	0	1	3895	0
99373	63	397	1	18	28394	0
86230	44	467	0	17	18632	0
30837	19	178	0	4	2325	0
31706	13	175	0	10	25139	0
89806	42	299	0	16	27975	0
62088	38	154	1	16	14483	0
40151	29	106	0	9	13127	0
27634	20	189	0	16	5839	0
76990	27	194	0	17	24069	0
37460	20	135	0	7	3738	0
54157	19	201	0	15	18625	0
49862	37	207	0	14	36341	0
84337	26	280	0	14	24548	0
64175	42	260	0	18	21792	0
59382	49	227	0	12	26263	0
119308	30	239	0	16	23686	0
76702	49	333	0	21	49303	0
103425	67	428	1	19	25659	0
70344	28	230	0	16	28904	0
43410	19	292	0	1	2781	0
104838	49	350	1	16	29236	0
62215	27	186	0	10	19546	0
69304	30	326	6	19	22818	0
53117	22	155	3	12	32689	0
19764	12	75	1	2	5752	0
86680	31	361	2	14	22197	0
84105	20	261	0	17	20055	0
77945	20	299	0	19	25272	0
89113	39	300	0	14	82206	0
91005	29	450	3	11	32073	0
40248	16	183	1	4	5444	0
64187	27	238	0	16	20154	0
50857	21	165	0	20	36944	0
56613	19	234	1	12	8019	0
62792	35	176	0	15	30884	0
72535	14	329	0	16	19540	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198368&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]3 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=198368&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198368&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=pearson)
TimeLoginsViewsSharedReviewedTotalSizePop
Time10.7160.8930.2940.7580.7460.591
Logins0.71610.6920.250.5490.5360.386
Views0.8930.69210.2820.6380.6270.507
Shared0.2940.250.28210.3890.3860.35
Reviewed0.7580.5490.6380.38910.7340.647
TotalSize0.7460.5360.6270.3860.73410.617
Pop0.5910.3860.5070.350.6470.6171

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Time & Logins & Views & Shared & Reviewed & TotalSize & Pop \tabularnewline
Time & 1 & 0.716 & 0.893 & 0.294 & 0.758 & 0.746 & 0.591 \tabularnewline
Logins & 0.716 & 1 & 0.692 & 0.25 & 0.549 & 0.536 & 0.386 \tabularnewline
Views & 0.893 & 0.692 & 1 & 0.282 & 0.638 & 0.627 & 0.507 \tabularnewline
Shared & 0.294 & 0.25 & 0.282 & 1 & 0.389 & 0.386 & 0.35 \tabularnewline
Reviewed & 0.758 & 0.549 & 0.638 & 0.389 & 1 & 0.734 & 0.647 \tabularnewline
TotalSize & 0.746 & 0.536 & 0.627 & 0.386 & 0.734 & 1 & 0.617 \tabularnewline
Pop & 0.591 & 0.386 & 0.507 & 0.35 & 0.647 & 0.617 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198368&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Time[/C][C]Logins[/C][C]Views[/C][C]Shared[/C][C]Reviewed[/C][C]TotalSize[/C][C]Pop[/C][/ROW]
[ROW][C]Time[/C][C]1[/C][C]0.716[/C][C]0.893[/C][C]0.294[/C][C]0.758[/C][C]0.746[/C][C]0.591[/C][/ROW]
[ROW][C]Logins[/C][C]0.716[/C][C]1[/C][C]0.692[/C][C]0.25[/C][C]0.549[/C][C]0.536[/C][C]0.386[/C][/ROW]
[ROW][C]Views[/C][C]0.893[/C][C]0.692[/C][C]1[/C][C]0.282[/C][C]0.638[/C][C]0.627[/C][C]0.507[/C][/ROW]
[ROW][C]Shared[/C][C]0.294[/C][C]0.25[/C][C]0.282[/C][C]1[/C][C]0.389[/C][C]0.386[/C][C]0.35[/C][/ROW]
[ROW][C]Reviewed[/C][C]0.758[/C][C]0.549[/C][C]0.638[/C][C]0.389[/C][C]1[/C][C]0.734[/C][C]0.647[/C][/ROW]
[ROW][C]TotalSize[/C][C]0.746[/C][C]0.536[/C][C]0.627[/C][C]0.386[/C][C]0.734[/C][C]1[/C][C]0.617[/C][/ROW]
[ROW][C]Pop[/C][C]0.591[/C][C]0.386[/C][C]0.507[/C][C]0.35[/C][C]0.647[/C][C]0.617[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198368&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198368&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)
TimeLoginsViewsSharedReviewedTotalSizePop
Time10.7160.8930.2940.7580.7460.591
Logins0.71610.6920.250.5490.5360.386
Views0.8930.69210.2820.6380.6270.507
Shared0.2940.250.28210.3890.3860.35
Reviewed0.7580.5490.6380.38910.7340.647
TotalSize0.7460.5360.6270.3860.73410.617
Pop0.5910.3860.5070.350.6470.6171







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Time;Logins0.7160.79820.609
p-value(0)(0)(0)
Time;Views0.89250.89950.726
p-value(0)(0)(0)
Time;Shared0.29410.32960.2453
p-value(0)(0)(0)
Time;Reviewed0.7580.78920.5899
p-value(0)(0)(0)
Time;TotalSize0.74620.81180.6171
p-value(0)(0)(0)
Time;Pop0.59090.61760.5052
p-value(0)(0)(0)
Logins;Views0.69190.80180.6142
p-value(0)(0)(0)
Logins;Shared0.25050.27950.2078
p-value(0)(0)(0)
Logins;Reviewed0.54880.62840.4525
p-value(0)(0)(0)
Logins;TotalSize0.53640.65880.4742
p-value(0)(0)(0)
Logins;Pop0.38570.43460.3574
p-value(0)(0)(0)
Views;Shared0.28210.33550.2476
p-value(0)(0)(0)
Views;Reviewed0.63770.69870.5025
p-value(0)(0)(0)
Views;TotalSize0.62670.71350.5211
p-value(0)(0)(0)
Views;Pop0.50710.54270.4441
p-value(0)(0)(0)
Shared;Reviewed0.38950.35110.2616
p-value(0)(0)(0)
Shared;TotalSize0.38610.40320.3007
p-value(0)(0)(0)
Shared;Pop0.34950.34690.3117
p-value(0)(0)(0)
Reviewed;TotalSize0.73450.78990.5825
p-value(0)(0)(0)
Reviewed;Pop0.64680.68690.5697
p-value(0)(0)(0)
TotalSize;Pop0.61680.64520.5277
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;Logins & 0.716 & 0.7982 & 0.609 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;Views & 0.8925 & 0.8995 & 0.726 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;Shared & 0.2941 & 0.3296 & 0.2453 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;Reviewed & 0.758 & 0.7892 & 0.5899 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;TotalSize & 0.7462 & 0.8118 & 0.6171 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;Pop & 0.5909 & 0.6176 & 0.5052 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Views & 0.6919 & 0.8018 & 0.6142 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Shared & 0.2505 & 0.2795 & 0.2078 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Reviewed & 0.5488 & 0.6284 & 0.4525 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;TotalSize & 0.5364 & 0.6588 & 0.4742 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Pop & 0.3857 & 0.4346 & 0.3574 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Views;Shared & 0.2821 & 0.3355 & 0.2476 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Views;Reviewed & 0.6377 & 0.6987 & 0.5025 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Views;TotalSize & 0.6267 & 0.7135 & 0.5211 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Views;Pop & 0.5071 & 0.5427 & 0.4441 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Shared;Reviewed & 0.3895 & 0.3511 & 0.2616 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Shared;TotalSize & 0.3861 & 0.4032 & 0.3007 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Shared;Pop & 0.3495 & 0.3469 & 0.3117 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Reviewed;TotalSize & 0.7345 & 0.7899 & 0.5825 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Reviewed;Pop & 0.6468 & 0.6869 & 0.5697 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
TotalSize;Pop & 0.6168 & 0.6452 & 0.5277 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198368&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;Logins[/C][C]0.716[/C][C]0.7982[/C][C]0.609[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;Views[/C][C]0.8925[/C][C]0.8995[/C][C]0.726[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;Shared[/C][C]0.2941[/C][C]0.3296[/C][C]0.2453[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;Reviewed[/C][C]0.758[/C][C]0.7892[/C][C]0.5899[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;TotalSize[/C][C]0.7462[/C][C]0.8118[/C][C]0.6171[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;Pop[/C][C]0.5909[/C][C]0.6176[/C][C]0.5052[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Views[/C][C]0.6919[/C][C]0.8018[/C][C]0.6142[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Shared[/C][C]0.2505[/C][C]0.2795[/C][C]0.2078[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Reviewed[/C][C]0.5488[/C][C]0.6284[/C][C]0.4525[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;TotalSize[/C][C]0.5364[/C][C]0.6588[/C][C]0.4742[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Pop[/C][C]0.3857[/C][C]0.4346[/C][C]0.3574[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Views;Shared[/C][C]0.2821[/C][C]0.3355[/C][C]0.2476[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Views;Reviewed[/C][C]0.6377[/C][C]0.6987[/C][C]0.5025[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Views;TotalSize[/C][C]0.6267[/C][C]0.7135[/C][C]0.5211[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Views;Pop[/C][C]0.5071[/C][C]0.5427[/C][C]0.4441[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Shared;Reviewed[/C][C]0.3895[/C][C]0.3511[/C][C]0.2616[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Shared;TotalSize[/C][C]0.3861[/C][C]0.4032[/C][C]0.3007[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Shared;Pop[/C][C]0.3495[/C][C]0.3469[/C][C]0.3117[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Reviewed;TotalSize[/C][C]0.7345[/C][C]0.7899[/C][C]0.5825[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Reviewed;Pop[/C][C]0.6468[/C][C]0.6869[/C][C]0.5697[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]TotalSize;Pop[/C][C]0.6168[/C][C]0.6452[/C][C]0.5277[/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=198368&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198368&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;Logins0.7160.79820.609
p-value(0)(0)(0)
Time;Views0.89250.89950.726
p-value(0)(0)(0)
Time;Shared0.29410.32960.2453
p-value(0)(0)(0)
Time;Reviewed0.7580.78920.5899
p-value(0)(0)(0)
Time;TotalSize0.74620.81180.6171
p-value(0)(0)(0)
Time;Pop0.59090.61760.5052
p-value(0)(0)(0)
Logins;Views0.69190.80180.6142
p-value(0)(0)(0)
Logins;Shared0.25050.27950.2078
p-value(0)(0)(0)
Logins;Reviewed0.54880.62840.4525
p-value(0)(0)(0)
Logins;TotalSize0.53640.65880.4742
p-value(0)(0)(0)
Logins;Pop0.38570.43460.3574
p-value(0)(0)(0)
Views;Shared0.28210.33550.2476
p-value(0)(0)(0)
Views;Reviewed0.63770.69870.5025
p-value(0)(0)(0)
Views;TotalSize0.62670.71350.5211
p-value(0)(0)(0)
Views;Pop0.50710.54270.4441
p-value(0)(0)(0)
Shared;Reviewed0.38950.35110.2616
p-value(0)(0)(0)
Shared;TotalSize0.38610.40320.3007
p-value(0)(0)(0)
Shared;Pop0.34950.34690.3117
p-value(0)(0)(0)
Reviewed;TotalSize0.73450.78990.5825
p-value(0)(0)(0)
Reviewed;Pop0.64680.68690.5697
p-value(0)(0)(0)
TotalSize;Pop0.61680.64520.5277
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')