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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 11 Dec 2012 19:50:35 -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/t1355273479g0o5n39c37a87qc.htm/, Retrieved Fri, 29 Mar 2024 04:51:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198747, Retrieved Fri, 29 Mar 2024 04:51:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [W10 PCM] [2012-12-12 00:50:35] [bc8de944878a372a2f96eab55bfa1be2] [Current]
- R P     [Kendall tau Correlation Matrix] [W10 - KCM] [2012-12-12 00:59:27] [3ae574fa1d645ef9b19cadb6c0dbd022]
- RMP     [Multiple Regression] [W10 MR] [2012-12-12 01:03:25] [3ae574fa1d645ef9b19cadb6c0dbd022]
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Dataseries X:
1418	210907	56	396	81	3	79
869	120982	56	297	55	4	58
1530	176508	54	559	50	12	60
2172	179321	89	967	125	2	108
901	123185	40	270	40	1	49
463	52746	25	143	37	3	0
3201	385534	92	1562	63	0	121
371	33170	18	109	44	0	1
1192	101645	63	371	88	0	20
1583	149061	44	656	66	5	43
1439	165446	33	511	57	0	69
1764	237213	84	655	74	0	78
1495	173326	88	465	49	7	86
1373	133131	55	525	52	7	44
2187	258873	60	885	88	3	104
1491	180083	66	497	36	9	63
4041	324799	154	1436	108	0	158
1706	230964	53	612	43	4	102
2152	236785	119	865	75	3	77
1036	135473	41	385	32	0	82
1882	202925	61	567	44	7	115
1929	215147	58	639	85	0	101
2242	344297	75	963	86	1	80
1220	153935	33	398	56	5	50
1289	132943	40	410	50	7	83
2515	174724	92	966	135	0	123
2147	174415	100	801	63	0	73
2352	225548	112	892	81	5	81
1638	223632	73	513	52	0	105
1222	124817	40	469	44	0	47
1812	221698	45	683	113	0	105
1677	210767	60	643	39	3	94
1579	170266	62	535	73	4	44
1731	260561	75	625	48	1	114
807	84853	31	264	33	4	38
2452	294424	77	992	59	2	107
829	101011	34	238	41	0	30
1940	215641	46	818	69	0	71
2662	325107	99	937	64	0	84
186	7176	17	70	1	0	0
1499	167542	66	507	59	2	59
865	106408	30	260	32	1	33
1793	96560	76	503	129	0	42
2527	265769	146	927	37	2	96
2747	269651	67	1269	31	10	106
1324	149112	56	537	65	6	56
2702	175824	107	910	107	0	57
1383	152871	58	532	74	5	59
1179	111665	34	345	54	4	39
2099	116408	61	918	76	1	34
4308	362301	119	1635	715	2	76
918	78800	42	330	57	2	20
1831	183167	66	557	66	0	91
3373	277965	89	1178	106	8	115
1713	150629	44	740	54	3	85
1438	168809	66	452	32	0	76
496	24188	24	218	20	0	8
2253	329267	259	764	71	8	79
744	65029	17	255	21	5	21
1161	101097	64	454	70	3	30
2352	218946	41	866	112	1	76
2144	244052	68	574	66	5	101
4691	341570	168	1276	190	1	94
1112	103597	43	379	66	1	27
2694	233328	132	825	165	5	92
1973	256462	105	798	56	0	123
1769	206161	71	663	61	12	75
3148	311473	112	1069	53	8	128
2474	235800	94	921	127	8	105
2084	177939	82	858	63	8	55
1954	207176	70	711	38	8	56
1226	196553	57	503	50	2	41
1389	174184	53	382	52	0	72
1496	143246	103	464	42	5	67
2269	187559	121	717	76	8	75
1833	187681	62	690	67	2	114
1268	119016	52	462	50	5	118
1943	182192	52	657	53	12	77
893	73566	32	385	39	6	22
1762	194979	62	577	50	7	66
1403	167488	45	619	77	2	69
1425	143756	46	479	57	0	105
1857	275541	63	817	73	4	116
1840	243199	75	752	34	3	88
1502	182999	88	430	39	6	73
1441	135649	46	451	46	2	99
1420	152299	53	537	63	0	62
1416	120221	37	519	35	1	53
2970	346485	90	1000	106	0	118
1317	145790	63	637	43	5	30
1644	193339	78	465	47	2	100
870	80953	25	437	31	0	49
1654	122774	45	711	162	0	24
1054	130585	46	299	57	5	67
937	112611	41	248	36	0	46
3004	286468	144	1162	263	1	57
2008	241066	82	714	78	0	75
2547	148446	91	905	63	1	135
1885	204713	71	649	54	1	68
1626	182079	63	512	63	2	124
1468	140344	53	472	77	6	33
2445	220516	62	905	79	1	98
1964	243060	63	786	110	4	58
1381	162765	32	489	56	2	68
1369	182613	39	479	56	3	81
1659	232138	62	617	43	0	131
2888	265318	117	925	111	10	110
1290	85574	34	351	71	0	37
2845	310839	92	1144	62	9	130
1982	225060	93	669	56	7	93
1904	232317	54	707	74	0	118
1391	144966	144	458	60	0	39
602	43287	14	214	43	4	13
1743	155754	61	599	68	4	74
1559	164709	109	572	53	0	81
2014	201940	38	897	87	0	109
2143	235454	73	819	46	0	151
2146	220801	75	720	105	1	51
874	99466	50	273	32	0	28
1590	92661	61	508	133	1	40
1590	133328	55	506	79	0	56
1210	61361	77	451	51	0	27
2072	125930	75	699	207	4	37
1281	100750	72	407	67	0	83
1401	224549	50	465	47	4	54
834	82316	32	245	34	4	27
1105	102010	53	370	66	3	28
1272	101523	42	316	76	0	59
1944	243511	71	603	65	0	133
391	22938	10	154	9	0	12
761	41566	35	229	42	5	0
1605	152474	65	577	45	0	106
530	61857	25	192	25	4	23
1988	99923	66	617	115	0	44
1386	132487	41	411	97	0	71
2395	317394	86	975	53	1	116
387	21054	16	146	2	0	4
1742	209641	42	705	52	5	62
620	22648	19	184	44	0	12
449	31414	19	200	22	0	18
800	46698	45	274	35	0	14
1684	131698	65	502	74	0	60
1050	91735	35	382	103	0	7
2699	244749	95	964	144	2	98
1606	184510	49	537	60	7	64
1502	79863	37	438	134	1	29
1204	128423	64	369	89	8	32
1138	97839	38	417	42	2	25
568	38214	34	276	52	0	16
1459	151101	32	514	98	2	48
2158	272458	65	822	99	0	100
1111	172494	52	389	52	0	46
1421	108043	62	466	29	1	45
2833	328107	65	1255	125	3	129
1955	250579	83	694	106	0	130
2922	351067	95	1024	95	3	136
1002	158015	29	400	40	0	59
1060	98866	18	397	140	0	25
956	85439	33	350	43	0	32
2186	229242	247	719	128	4	63
3604	351619	139	1277	142	4	95
1035	84207	29	356	73	11	14
1417	120445	118	457	72	0	36
3261	324598	110	1402	128	0	113
1587	131069	67	600	61	4	47
1424	204271	42	480	73	0	92
1701	165543	65	595	148	1	70
1249	141722	94	436	64	0	19
946	116048	64	230	45	0	50
1926	250047	81	651	58	0	41
3352	299775	95	1367	97	9	91
1641	195838	67	564	50	1	111
2035	173260	63	716	37	3	41
2312	254488	83	747	50	10	120
1369	104389	45	467	105	5	135
1577	136084	30	671	69	0	27
2201	199476	70	861	46	2	87
961	92499	32	319	57	0	25
1900	224330	83	612	52	1	131
1254	135781	31	433	98	2	45
1335	74408	67	434	61	4	29
1597	81240	66	503	89	0	58
207	14688	10	85	0	0	4
1645	181633	70	564	48	2	47
2429	271856	103	824	91	1	109
151	7199	5	74	0	0	7
474	46660	20	259	7	0	12
141	17547	5	69	3	0	0
1639	133368	36	535	54	1	37
872	95227	34	239	70	0	37
1318	152601	48	438	36	2	46
1018	98146	40	459	37	0	15
1383	79619	43	426	123	3	42
1314	59194	31	288	247	6	7
1335	139942	42	498	46	0	54
1403	118612	46	454	72	2	54
910	72880	33	376	41	0	14
616	65475	18	225	24	2	16
1407	99643	55	555	45	1	33
771	71965	35	252	33	1	32
766	77272	59	208	27	2	21
473	49289	19	130	36	1	15
1376	135131	66	481	87	0	38
1232	108446	60	389	90	1	22
1521	89746	36	565	114	3	28
572	44296	25	173	31	0	10
1059	77648	47	278	45	0	31
1544	181528	54	609	69	0	32
1230	134019	53	422	51	0	32
1206	124064	40	445	34	1	43
1205	92630	40	387	60	4	27
1255	121848	39	339	45	0	37
613	52915	14	181	54	0	20
721	81872	45	245	25	0	32
1109	58981	36	384	38	7	0
740	53515	28	212	52	2	5
1126	60812	44	399	67	0	26
728	56375	30	229	74	7	10
689	65490	22	224	38	3	27
592	80949	17	203	30	0	11
995	76302	31	333	26	0	29
1613	104011	55	384	67	6	25
2048	98104	54	636	132	2	55
705	67989	21	185	42	0	23
301	30989	14	93	35	0	5
1803	135458	81	581	118	3	43
799	73504	35	248	68	0	23
861	63123	43	304	43	1	34
1186	61254	46	344	76	1	36
1451	74914	30	407	64	0	35
628	31774	23	170	48	1	0
1161	81437	38	312	64	0	37
1463	87186	54	507	56	0	28
742	50090	20	224	71	0	16
979	65745	53	340	75	0	26
675	56653	45	168	39	0	38
1241	158399	39	443	42	0	23
676	46455	20	204	39	0	22
1049	73624	24	367	93	0	30
620	38395	31	210	38	0	16
1081	91899	35	335	60	0	18
1688	139526	151	364	71	0	28
736	52164	52	178	52	0	32
617	51567	30	206	27	2	21
812	70551	31	279	59	0	23
1051	84856	29	387	40	1	29
1656	102538	57	490	79	1	50
705	86678	40	238	44	0	12
945	85709	44	343	65	0	21
554	34662	25	232	10	0	18
1597	150580	77	530	124	0	27
982	99611	35	291	81	0	41
222	19349	11	67	15	0	13
1212	99373	63	397	92	1	12
1143	86230	44	467	42	0	21
435	30837	19	178	10	0	8
532	31706	13	175	24	0	26
882	89806	42	299	64	0	27
608	62088	38	154	45	1	13
459	40151	29	106	22	0	16
578	27634	20	189	56	0	2
826	76990	27	194	94	0	42
509	37460	20	135	19	0	5
717	54157	19	201	35	0	37
637	49862	37	207	32	0	17
857	84337	26	280	35	0	38
830	64175	42	260	48	0	37
652	59382	49	227	49	0	29
707	119308	30	239	48	0	32
954	76702	49	333	62	0	35
1461	103425	67	428	96	1	17
672	70344	28	230	45	0	20
778	43410	19	292	63	0	7
1141	104838	49	350	71	1	46
680	62215	27	186	26	0	24
1090	69304	30	326	48	6	40
616	53117	22	155	29	3	3
285	19764	12	75	19	1	10
1145	86680	31	361	45	2	37
733	84105	20	261	45	0	17
888	77945	20	299	67	0	28
849	89113	39	300	30	0	19
1182	91005	29	450	36	3	29
528	40248	16	183	34	1	8
642	64187	27	238	36	0	10
947	50857	21	165	34	0	15
819	56613	19	234	37	1	15
757	62792	35	176	46	0	28
894	72535	14	329	44	0	17




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=198747&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=198747&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198747&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)
pageviewstime_in_rfcloginscompendium_views_infocompendium_views_prshared_compendiumsblogged_computations
pageviews10.8930.7590.9620.5630.2970.761
time_in_rfc0.89310.7160.8930.390.2940.831
logins0.7590.71610.6920.3880.250.566
compendium_views_info0.9620.8930.69210.5190.2820.749
compendium_views_pr0.5630.390.3880.51910.0640.229
shared_compendiums0.2970.2940.250.2820.06410.238
blogged_computations0.7610.8310.5660.7490.2290.2381

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & pageviews & time_in_rfc & logins & compendium_views_info & compendium_views_pr & shared_compendiums & blogged_computations \tabularnewline
pageviews & 1 & 0.893 & 0.759 & 0.962 & 0.563 & 0.297 & 0.761 \tabularnewline
time_in_rfc & 0.893 & 1 & 0.716 & 0.893 & 0.39 & 0.294 & 0.831 \tabularnewline
logins & 0.759 & 0.716 & 1 & 0.692 & 0.388 & 0.25 & 0.566 \tabularnewline
compendium_views_info & 0.962 & 0.893 & 0.692 & 1 & 0.519 & 0.282 & 0.749 \tabularnewline
compendium_views_pr & 0.563 & 0.39 & 0.388 & 0.519 & 1 & 0.064 & 0.229 \tabularnewline
shared_compendiums & 0.297 & 0.294 & 0.25 & 0.282 & 0.064 & 1 & 0.238 \tabularnewline
blogged_computations & 0.761 & 0.831 & 0.566 & 0.749 & 0.229 & 0.238 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198747&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]pageviews[/C][C]time_in_rfc[/C][C]logins[/C][C]compendium_views_info[/C][C]compendium_views_pr[/C][C]shared_compendiums[/C][C]blogged_computations[/C][/ROW]
[ROW][C]pageviews[/C][C]1[/C][C]0.893[/C][C]0.759[/C][C]0.962[/C][C]0.563[/C][C]0.297[/C][C]0.761[/C][/ROW]
[ROW][C]time_in_rfc[/C][C]0.893[/C][C]1[/C][C]0.716[/C][C]0.893[/C][C]0.39[/C][C]0.294[/C][C]0.831[/C][/ROW]
[ROW][C]logins[/C][C]0.759[/C][C]0.716[/C][C]1[/C][C]0.692[/C][C]0.388[/C][C]0.25[/C][C]0.566[/C][/ROW]
[ROW][C]compendium_views_info[/C][C]0.962[/C][C]0.893[/C][C]0.692[/C][C]1[/C][C]0.519[/C][C]0.282[/C][C]0.749[/C][/ROW]
[ROW][C]compendium_views_pr[/C][C]0.563[/C][C]0.39[/C][C]0.388[/C][C]0.519[/C][C]1[/C][C]0.064[/C][C]0.229[/C][/ROW]
[ROW][C]shared_compendiums[/C][C]0.297[/C][C]0.294[/C][C]0.25[/C][C]0.282[/C][C]0.064[/C][C]1[/C][C]0.238[/C][/ROW]
[ROW][C]blogged_computations[/C][C]0.761[/C][C]0.831[/C][C]0.566[/C][C]0.749[/C][C]0.229[/C][C]0.238[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198747&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198747&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)
pageviewstime_in_rfcloginscompendium_views_infocompendium_views_prshared_compendiumsblogged_computations
pageviews10.8930.7590.9620.5630.2970.761
time_in_rfc0.89310.7160.8930.390.2940.831
logins0.7590.71610.6920.3880.250.566
compendium_views_info0.9620.8930.69210.5190.2820.749
compendium_views_pr0.5630.390.3880.51910.0640.229
shared_compendiums0.2970.2940.250.2820.06410.238
blogged_computations0.7610.8310.5660.7490.2290.2381







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
pageviews;time_in_rfc0.89280.90250.7387
p-value(0)(0)(0)
pageviews;logins0.75880.8450.6609
p-value(0)(0)(0)
pageviews;compendium_views_info0.96250.96650.8489
p-value(0)(0)(0)
pageviews;compendium_views_pr0.56330.63320.4628
p-value(0)(0)(0)
pageviews;shared_compendiums0.29720.3410.2511
p-value(0)(0)(0)
pageviews;blogged_computations0.76060.82490.6272
p-value(0)(0)(0)
time_in_rfc;logins0.7160.79820.609
p-value(0)(0)(0)
time_in_rfc;compendium_views_info0.89250.89950.726
p-value(0)(0)(0)
time_in_rfc;compendium_views_pr0.39030.4890.3435
p-value(0)(0)(0)
time_in_rfc;shared_compendiums0.29410.32960.2453
p-value(0)(0)(0)
time_in_rfc;blogged_computations0.83090.87170.683
p-value(0)(0)(0)
logins;compendium_views_info0.69190.80180.6142
p-value(0)(0)(0)
logins;compendium_views_pr0.38820.52260.3788
p-value(0)(0)(0)
logins;shared_compendiums0.25050.27950.2078
p-value(0)(0)(0)
logins;blogged_computations0.56610.71780.523
p-value(0)(0)(0)
compendium_views_info;compendium_views_pr0.51860.58490.4206
p-value(0)(0)(0)
compendium_views_info;shared_compendiums0.28210.33550.2476
p-value(0)(0)(0)
compendium_views_info;blogged_computations0.74890.80510.6045
p-value(0)(0)(0)
compendium_views_pr;shared_compendiums0.06390.12630.094
p-value(0.2787)(0.0319)(0.0308)
compendium_views_pr;blogged_computations0.22890.41730.2892
p-value(1e-04)(0)(0)
shared_compendiums;blogged_computations0.2380.27590.2074
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
pageviews;time_in_rfc & 0.8928 & 0.9025 & 0.7387 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pageviews;logins & 0.7588 & 0.845 & 0.6609 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pageviews;compendium_views_info & 0.9625 & 0.9665 & 0.8489 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pageviews;compendium_views_pr & 0.5633 & 0.6332 & 0.4628 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pageviews;shared_compendiums & 0.2972 & 0.341 & 0.2511 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pageviews;blogged_computations & 0.7606 & 0.8249 & 0.6272 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;logins & 0.716 & 0.7982 & 0.609 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;compendium_views_info & 0.8925 & 0.8995 & 0.726 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;compendium_views_pr & 0.3903 & 0.489 & 0.3435 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;shared_compendiums & 0.2941 & 0.3296 & 0.2453 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time_in_rfc;blogged_computations & 0.8309 & 0.8717 & 0.683 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
logins;compendium_views_info & 0.6919 & 0.8018 & 0.6142 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
logins;compendium_views_pr & 0.3882 & 0.5226 & 0.3788 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
logins;shared_compendiums & 0.2505 & 0.2795 & 0.2078 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
logins;blogged_computations & 0.5661 & 0.7178 & 0.523 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
compendium_views_info;compendium_views_pr & 0.5186 & 0.5849 & 0.4206 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
compendium_views_info;shared_compendiums & 0.2821 & 0.3355 & 0.2476 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
compendium_views_info;blogged_computations & 0.7489 & 0.8051 & 0.6045 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
compendium_views_pr;shared_compendiums & 0.0639 & 0.1263 & 0.094 \tabularnewline
p-value & (0.2787) & (0.0319) & (0.0308) \tabularnewline
compendium_views_pr;blogged_computations & 0.2289 & 0.4173 & 0.2892 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
shared_compendiums;blogged_computations & 0.238 & 0.2759 & 0.2074 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198747&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]pageviews;time_in_rfc[/C][C]0.8928[/C][C]0.9025[/C][C]0.7387[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pageviews;logins[/C][C]0.7588[/C][C]0.845[/C][C]0.6609[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pageviews;compendium_views_info[/C][C]0.9625[/C][C]0.9665[/C][C]0.8489[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pageviews;compendium_views_pr[/C][C]0.5633[/C][C]0.6332[/C][C]0.4628[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pageviews;shared_compendiums[/C][C]0.2972[/C][C]0.341[/C][C]0.2511[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pageviews;blogged_computations[/C][C]0.7606[/C][C]0.8249[/C][C]0.6272[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time_in_rfc;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_in_rfc;compendium_views_info[/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_in_rfc;compendium_views_pr[/C][C]0.3903[/C][C]0.489[/C][C]0.3435[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time_in_rfc;shared_compendiums[/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_in_rfc;blogged_computations[/C][C]0.8309[/C][C]0.8717[/C][C]0.683[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]logins;compendium_views_info[/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;compendium_views_pr[/C][C]0.3882[/C][C]0.5226[/C][C]0.3788[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]logins;shared_compendiums[/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;blogged_computations[/C][C]0.5661[/C][C]0.7178[/C][C]0.523[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]compendium_views_info;compendium_views_pr[/C][C]0.5186[/C][C]0.5849[/C][C]0.4206[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]compendium_views_info;shared_compendiums[/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]compendium_views_info;blogged_computations[/C][C]0.7489[/C][C]0.8051[/C][C]0.6045[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]compendium_views_pr;shared_compendiums[/C][C]0.0639[/C][C]0.1263[/C][C]0.094[/C][/ROW]
[ROW][C]p-value[/C][C](0.2787)[/C][C](0.0319)[/C][C](0.0308)[/C][/ROW]
[ROW][C]compendium_views_pr;blogged_computations[/C][C]0.2289[/C][C]0.4173[/C][C]0.2892[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]shared_compendiums;blogged_computations[/C][C]0.238[/C][C]0.2759[/C][C]0.2074[/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=198747&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198747&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
pageviews;time_in_rfc0.89280.90250.7387
p-value(0)(0)(0)
pageviews;logins0.75880.8450.6609
p-value(0)(0)(0)
pageviews;compendium_views_info0.96250.96650.8489
p-value(0)(0)(0)
pageviews;compendium_views_pr0.56330.63320.4628
p-value(0)(0)(0)
pageviews;shared_compendiums0.29720.3410.2511
p-value(0)(0)(0)
pageviews;blogged_computations0.76060.82490.6272
p-value(0)(0)(0)
time_in_rfc;logins0.7160.79820.609
p-value(0)(0)(0)
time_in_rfc;compendium_views_info0.89250.89950.726
p-value(0)(0)(0)
time_in_rfc;compendium_views_pr0.39030.4890.3435
p-value(0)(0)(0)
time_in_rfc;shared_compendiums0.29410.32960.2453
p-value(0)(0)(0)
time_in_rfc;blogged_computations0.83090.87170.683
p-value(0)(0)(0)
logins;compendium_views_info0.69190.80180.6142
p-value(0)(0)(0)
logins;compendium_views_pr0.38820.52260.3788
p-value(0)(0)(0)
logins;shared_compendiums0.25050.27950.2078
p-value(0)(0)(0)
logins;blogged_computations0.56610.71780.523
p-value(0)(0)(0)
compendium_views_info;compendium_views_pr0.51860.58490.4206
p-value(0)(0)(0)
compendium_views_info;shared_compendiums0.28210.33550.2476
p-value(0)(0)(0)
compendium_views_info;blogged_computations0.74890.80510.6045
p-value(0)(0)(0)
compendium_views_pr;shared_compendiums0.06390.12630.094
p-value(0.2787)(0.0319)(0.0308)
compendium_views_pr;blogged_computations0.22890.41730.2892
p-value(1e-04)(0)(0)
shared_compendiums;blogged_computations0.2380.27590.2074
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')