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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, 28 Dec 2010 23:32:21 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/29/t1293579087067m9manf5prrvs.htm/, Retrieved Fri, 03 May 2024 09:12:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116587, Retrieved Fri, 03 May 2024 09:12:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Paper Correlation...] [2010-12-28 23:32:21] [21ba15a181629d0f70ea456ec39a7075] [Current]
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Dataseries X:
8.155	14.296	133	19.573
278.295	469.137	94	13.804
7.014	12.242	117	17.224
9.682	16.380	100	14.634
6.196	10.178	111	16.378
21.303	37.161	122	17.943
15.031	26.949	109	16.013
12.637	21.502	126	18.559
9.353	17.279	99	14.479
5.606	9.808	107	15.726
4.581	8.312	138	20.202
9.655	17.541	113	16.608
14.851	26.173	123	18.126
11.332	20.266	122	17.923
4.509	8.062	117	17.127
8.043	14.191	107	15.687
14.626	24.423	118	17.389
5.377	9.038	102	15.016
10.169	18.004	114	16.792
8.452	14.671	116	17.073
4.503	7.974	113	16.639
10.763	19.526	131	19.183
19.207	33.194	114	16.816
10.194	17.682	118	17.296
5.282	8.888	112	16.470
7.120	12.152	111	16.367
10.374	18.721	100	14.764
7.099	12.301	113	16.530
11.843	20.903	118	17.395
11.191	18.386	116	17.027
6.202	10.699	104	15.346
8.259	14.528	130	19.150
11.673	20.291	114	16.731
9.642	16.187	113	16.555
23.073	38.960	105	15.444
20.102	33.375	111	16.238
47.035	79.201	106	15.607
12.181	21.094	104	15.305
9.293	15.860	108	15.866
9.341	16.324	114	16.778
4.389	7.853	109	16.071
11.293	19.809	111	16.360
13.594	23.482	105	15.369
6.969	12.423	95	14.026
1.306	2.361	94	13.780
11.855	20.511	102	14.993
9.266	16.678	108	15.892
4.983	8.898	100	14.749
21.305	35.758	108	15.835
6.105	10.808	110	16.087
16.081	26.210	108	15.796
4.980	8.498	103	15.190
8.225	14.018	103	15.153
10.576	19.049	98	14.458
5.576	9.482	105	15.360
10.143	18.020	106	15.584
8.884	15.039	104	15.207
8.985	15.716	105	15.432
5.634	9.520	106	15.552
4.485	8.295	101	14.851
19.285	33.230	106	15.557
6.678	11.507	108	15.858
7.101	12.655	112	16.401
7.739	14.079	95	13.941
5.742	10.515	98	14.427
6.192	10.914	95	13.912
24.554	39.966	103	15.194
4.386	7.409	103	15.146
5.697	10.231	120	17.576
13.625	23.331	109	15.960
55.457	98.343	75	10.980
16.181	29.883	107	15.669
11.927	20.703	99	14.554
79.009	147.395	76	11.237
21.129	42.622	81	11.836
19.132	34.427	86	12.651
27.088	48.595	87	12.749
13.241	21.569	97	14.227
41.602	78.928	88	12.897
26.141	44.082	93	13.602
10.678	18.780	82	12.059
42.356	82.653	65	9.496
23.658	45.001	69	10.126
11.936	23.931	55	8.100
59.836	114.766	72	10.518
39.267	76.654	110	16.101
13.664	24.127	113	16.628
25.699	48.788	102	14.940
19.016	38.602	114	16.719
6.849	12.199	118	17.379
16.942	29.446	116	17.066
12.988	23.582	120	17.652
1.130	2.070	112	16.435
22.943	39.619	123	18.074
2.835	4.857	99	14.546
4.732	8.221	116	17.085
5.016	8.905	119	17.517
20.042	34.423	127	18.613
20.786	35.229	111	16.257
3.666	6.524	114	16.746
5.381	10.142	120	17.593
6.272	11.075	125	18.415
5.235	8.942	120	17.629
6.097	13.092	119	17.446
4.931	8.738	127	18.693
7.093	12.162	110	16.149
2.664	4.715	123	18.125
10.084	17.488	117	17.217
7.252	12.872	102	15.044
10.439	18.505	135	19.792
8.663	15.081	116	17.012
7.147	12.484	119	17.443
12.040	24.279	123	18.024
2.479	4.379	122	17.955
6.110	10.861	116	17.069
9.125	17.998	135	19.777
17.724	31.024	107	15.756
6.361	11.094	126	18.557
8.481	14.773	120	17.659
21.670	38.260	104	15.314
8.455	14.956	125	18.294
6.431	13.515	119	17.543
15.695	29.267	111	16.322
12.215	21.626	129	19.020
16.985	28.075	112	16.459
5.509	9.557	112	16.453
3.349	5.920	104	15.257
5.100	9.365	123	18.042
5.098	9.256	128	18.799
6.498	11.617	129	18.907
4.213	7.528	125	18.364
13.679	22.935	108	15.869
3.339	5.811	102	14.936
2.865	5.231	111	16.293
7.810	13.811	118	17.378
10.848	19.479	131	19.293
3.560	6.291	119	17.547
5.120	9.427	122	17.955
4.994	9.280	121	17.780
6.921	12.608	142	20.906
4.308	7.582	105	15.361
10.372	18.543	125	18.361
8.788	14.967	112	16.471
55.767	92.323	118	17.289
4.019	7.043	111	16.299
7.486	13.762	131	19.288
5.889	10.899	138	20.228
8.479	15.222	120	17.668
13.187	22.208	107	15.654
9.933	20.892	120	17.612
5.821	10.161	113	16.607
19.645	32.145	110	16.143
7.991	13.977	115	16.870
4.779	8.015	106	15.506
3.602	6.608	117	17.222
21.505	37.620	120	17.653
5.378	9.548	113	16.574
3.641	6.855	119	17.439
5.885	11.099	126	18.449
5.154	9.577	112	16.437
7.978	14.341	114	16.700
6.874	12.540	126	18.500
1.784	3.128	107	15.673
2.514	4.679	111	16.298
3.423	6.112	114	16.739
7.271	12.703	107	15.671
3.965	7.326	123	18.075
7.124	14.018	139	20.448
3.645	6.586	117	17.116
15.202	24.828	115	16.931
4.408	7.993	107	15.695
16.341	30.235	103	15.135
4.294	7.697	110	16.126
3.175	5.900	105	15.462
5.761	10.246	104	15.242
11.727	21.498	124	18.159
13.005	22.829	97	14.226
5.386	9.778	113	16.536
3.269	6.124	121	17.751
14.968	29.423	116	17.095
18.943	32.680	114	16.706
8.405	14.748	104	15.282
12.020	18.389	97	14.314
70.511	117.027	108	15.823
6.158	10.864	102	14.918
7.398	13.645	108	15.843
21.308	34.079	133	19.477
12.316	22.029	106	15.514
11.570	19.647	101	14.889
11.978	22.000	100	14.699
1.546	2.755	107	15.663
9.130	15.881	90	13.183
5.226	9.205	87	12.722
4.837	8.333	92	13.448
6.837	12.039	91	13.358
1.839	3.331	81	11.891
4.550	8.172	83	12.135
20.470	34.865	95	14.030
4.273	7.783	88	12.938
560	990	78	11.519
11.147	19.772	90	13.197
2.042	3.656	80	11.769
10.107	17.732	92	13.462
6.693	12.000	91	13.413
7.696	14.110	102	14.966
5.520	9.560	98	14.371
6.305	11.327	101	14.797
15.090	26.311	99	14.607
43.413	73.859	103	15.168
7.131	12.637	99	14.599
3.092	5.439	99	14.556
18.743	32.444	91	13.417
1.138	2.048	92	13.573
20.382	35.897	103	15.112
17.304	30.928	99	14.517
13.142	23.853	102	15.022
9.196	15.460	102	14.965
7.585	12.210	108	15.926
6.365	11.277	96	14.100
7.570	13.533	92	13.539
11.344	18.229	96	14.117
45.037	69.145	100	14.636
5.037	8.951	98	14.354
5.425	9.897	97	14.217
5.923	10.633	97	14.182
15.461	26.633	101	14.775
5.195	9.375	94	13.745
4.642	8.463	97	14.254
6.105	10.768	93	13.704
32.793	56.407	102	14.965
6.098	11.017	88	12.996
5.197	9.098	96	14.140
4.161	8.207	93	13.727
6.140	11.007	92	13.545
4.092	7.480	94	13.881
3.597	6.597	94	13.777
2.885	5.133	95	13.903
10.799	19.415	100	14.672
4.972	9.047	94	13.876
7.354	13.394	93	13.654
2.746	4.959	83	12.205
6.520	10.219	95	13.968
13.284	21.467	130	19.027
6.979	11.001	98	14.375
6.922	11.790	93	13.589
47.352	78.030	111	16.324
10.535	17.715	112	16.442
11.341	19.128	117	17.130
18.588	31.605	105	15.498
10.325	17.485	115	16.868
9.841	16.910	112	16.509
9.930	17.334	114	16.678
21.171	36.046	109	15.940
5.516	9.507	109	16.023
14.675	24.619	116	16.998
8.212	14.362	107	15.734
8.027	13.931	114	16.803
25.978	43.569	107	15.730
13.565	23.457	98	14.362
6.887	11.809	115	16.899
10.218	17.647	107	15.704
5.733	10.320	118	17.368
14.076	23.359	109	15.985
6.197	11.081	110	16.216
11.413	20.450	97	14.246
7.861	13.610	104	15.291
12.047	19.735	101	14.832
3.494	6.171	106	15.632
12.806	22.381	99	14.592
3.800	6.591	99	14.513
7.337	12.216	102	15.027
10.494	18.957	108	15.910
5.660	10.262	139	20.393
16.514	28.696	108	15.806
9.992	17.345	120	17.691
18.510	32.459	110	16.126
6.947	12.202	113	16.593
145.933	236.196	105	15.391
4.574	7.946	99	14.576
11.405	20.564	115	16.838
5.257	9.405	118	17.358
6.127	10.685	116	17.048
12.857	22.564	121	17.845
3.343	5.923	108	15.888
6.343	11.021	113	16.618
6.317	11.403	108	15.841
7.342	13.217	114	16.701
4.605	8.253	152	22.269
4.506	7.766	103	15.095
4.008	6.950	109	15.959
4.658	8.018	105	15.367
8.334	14.671	102	14.979
8.154	13.820	109	15.964
1.143	2.063	109	16.059
3.608	6.320	101	14.833
4.462	8.150	108	15.813
3.623	6.464	110	16.226
3.699	6.453	107	15.782
17.103	28.935	109	15.996
13.826	24.532	87	12.736
3.366	6.110	111	16.249
3.932	6.887	108	15.901
4.406	7.877	111	16.343
25.953	45.829	111	16.337
8.746	15.408	107	15.747
21.624	38.382	101	14.822
10.162	18.275	105	15.374
41.500	70.233	102	15.004
9.663	17.068	103	15.127
15.252	26.976	105	15.430
16.211	27.363	100	14.706
7.783	13.492	90	13.274
6.593	11.562	86	12.680
1.932	3.391	94	13.775
3.561	6.369	96	14.067
3.317	5.747	101	14.888
1.905	3.278	100	14.654
6.355	11.071	95	13.995
5.976	10.720	85	12.529
8.174	14.142	83	12.240
117.696	201.571	78	11.433
20.776	35.784	78	11.482
17.180	29.879	85	12.512
6.020	11.034	70	10.226
12.990	22.269	87	12.840
9.788	16.775	84	12.384
6.853	12.048	114	16.795
5.112	8.963	106	15.607
12.900	22.421	84	12.274
6.021	10.192	115	16.905
9.198	16.423	102	14.971
6.033	10.677	102	14.946
11.794	20.155	79	11.629
11.416	20.021	74	10.941
9.873	16.890	83	12.123
12.235	20.728	86	12.630
3.810	6.728	84	12.331
2.843	5.017	95	13.905
4.920	9.720	105	15.369
2.187	4.080	97	14.254
53.206	91.174	89	13.011
10.872	18.714	78	11.447
4.402	7.746	102	15.029
3.940	6.556	83	12.215
13.356	22.622	93	13.643
9.899	17.597	82	12.015
30.531	53.467	84	12.336
11.700	20.620	102	14.933
5.871	10.207	99	14.506
7.185	12.387	109	16.084
44.601	77.562	83	12.134
4.475	7.994	102	14.971
10.543	18.085	94	13.874
4.321	8.042	110	16.202
14.135	25.785	96	14.079
6.825	11.632	82	12.102
3.782	6.755	87	12.798
19.290	32.591	87	12.713
5.622	9.898	79	11.559
5.501	9.588	82	12.085
4.216	7.455	93	13.627
2.085	3.604	81	11.893
7.508	13.377	114	16.791
3.083	5.550	101	14.790
2.187	4.130	83	12.129
2.914	5.148	75	11.016
11.033	18.768	85	12.556
2.657	4.688	84	12.363
8.308	14.640	102	14.943
4.482	7.550	88	12.947
4.325	7.726	88	12.937
3.056	5.449	91	13.430
5.351	9.826	90	13.216
7.756	13.315	93	13.721
1.918	3.423	95	13.997
2.933	5.324	92	13.548
9.489	16.883	82	12.087
2.888	5.046	91	13.368
40.378	68.018	94	13.788
7.744	13.213	92	13.543
2.261	4.007	104	15.341
1.583	2.870	104	15.319
2.380	4.238	96	14.168
3.280	5.742	86	12.691
2.551	4.519	96	14.045
2.116	3.618	93	13.695
2.532	4.593	100	14.646
12.499	20.263	93	13.722
2.896	5.151	95	14.021
2.091	3.736	103	15.122
3.169	5.669	118	17.390
1.487	2.582	97	14.321
1.288	2.397	102	15.047
1.946	3.650	105	15.422
3.374	6.142	99	14.491
7.220	12.870	101	14.792
16.349	27.483	94	13.826
4.996	8.737	105	15.358
6.435	11.160	95	13.886
4.905	8.439	97	14.201
6.779	11.798	91	13.363
7.304	12.932	106	15.569
11.935	20.934	123	18.061
3.173	5.383	88	12.898
3.677	6.616	108	15.890
7.851	13.069	113	16.556
14.750	24.992	89	13.136
9.395	16.150	94	13.751
12.687	21.833	86	12.615
22.124	37.702	82	12.102
4.886	8.555	107	15.728
112.237	189.504	85	12.439
5.420	9.716	127	18.611
13.897	23.651	96	14.067
13.110	22.591	79	11.556
36.631	61.447	81	11.932
8.813	15.654	97	14.234
7.325	13.080	107	15.725
4.334	7.718	97	14.213
9.665	16.877	92	13.573
2.352	4.156	99	14.498
2.307	4.133	97	14.318
8.020	14.467	75	10.952
9.416	16.747	99	14.597
4.524	8.022	107	15.685
1.873	3.351	90	13.158
3.194	5.662	91	13.312
6.869	11.910	92	13.571
2.099	3.785	118	17.363
5.376	9.574	90	13.211
5.404	9.773	88	12.967
6.601	10.510	96	14.036
3.926	6.687	91	13.386
1.688	3.010	101	14.849
6.668	11.717	102	15.051
2.837	5.380	104	15.237
1.452	2.516	90	13.255
31.389	54.334	82	12.019
3.784	6.820	89	13.004
5.429	9.290	96	14.109
2.686	5.338	83	12.250
2.601	5.462	79	11.634
1.996	3.952	82	12.084
2.930	5.597	82	12.070
9.787	18.360	98	14.437
5.359	10.519	84	12.291
2.611	5.221	93	13.664
5.028	10.255	97	14.230
4.939	9.216	93	13.589
1.565	2.833	104	15.294
3.166	5.639	102	15.010
1.601	2.867	110	16.195
1.574	2.859	111	16.338
1.988	3.577	110	16.218
1.732	3.056	104	15.233
1.585	2.962	105	15.403
8.232	14.596	105	15.455
1.738	3.047	104	15.335
2.003	3.506	105	15.366
2.944	5.164	109	15.965
3.847	6.563	91	13.437
8.635	14.252	104	15.286
1.424	2.581	94	13.821
4.251	7.592	99	14.599
23.050	41.757	92	13.570
10.052	17.937	105	15.437
35.964	64.194	89	13.023
4.536	7.922	103	15.160
5.056	8.745	103	15.070
5.611	9.899	101	14.853
43.970	71.063	112	16.460
6.788	11.916	105	15.395
17.047	31.147	93	13.713
8.488	14.554	96	14.071
7.928	13.905	104	15.311
3.879	6.696	99	14.577
5.280	9.762	97	14.269
23.525	38.627	103	15.102
9.981	17.113	107	15.785
11.471	20.183	103	15.061
3.918	6.970	101	14.859
6.876	12.535	89	13.140
8.429	14.644	97	14.210
10.793	19.233	91	13.345
7.693	13.880	90	13.157
6.390	11.564	95	13.934
16.513	30.021	89	13.091
6.516	12.108	89	13.021
17.937	32.282	95	13.927
13.589	24.009	96	14.072
6.857	12.637	95	13.908
9.005	16.201	96	14.170
7.427	13.650	95	13.993
9.015	15.969	97	14.200
6.216	11.121	105	15.470
17.455	30.278	98	14.327
6.014	10.272	101	14.778
3.978	6.855	98	14.356
56	84	117	17.213
5.409	9.377	100	14.699
4.685	8.152	104	15.302
14.213	24.829	101	14.801
20.890	36.558	86	12.655
8.987	16.110	96	14.140
17.813	29.832	101	14.853
2.298	4.234	93	13.651
4.065	7.050	102	15.047
14.443	26.738	119	17.495
2.249	4.873	122	17.969
8.045	15.263	97	14.211
883	1.575	95	13.964
3.955	7.543	118	17.334
7.905	14.481	88	12.997
1.576	3.025	85	12.454
1.073	2.093	103	15.123
2.606	4.803	82	12.043
2.755	4.810	87	12.748
1.310	2.325	85	12.544
2.487	4.817	87	12.844
4.285	7.372	89	13.091
6.276	10.706	86	12.697
1.672	2.948	86	12.667
2.807	5.076	83	12.150
2.521	4.349	82	11.993
1.869	3.207	89	13.102
9.606	17.100	88	12.948
2.772	5.069	88	12.984
1.371	2.316	83	12.213
1.469	2.585	90	13.150
4.678	8.187	88	12.989
3.278	5.489	85	12.427
778	1.369	86	12.563
893	1.547	87	12.718
2.216	4.259	93	13.676
2.623	4.681	92	13.554
5.567	10.016	95	13.897
3.660	6.676	90	13.240
2.829	5.072	84	12.327
3.294	5.774	90	13.250
1.321	2.392	89	13.019
1.630	2.974	83	12.255
2.758	5.071	91	13.297
2.641	5.429	111	16.308
3.259	5.447	87	12.801
4.097	7.964	108	15.891
1.474	2.699	92	13.533
2.167	4.264	97	14.205
1.080	2.037	86	12.631
1.647	3.212	107	15.668
1.907	3.758	91	13.332
5.890	11.230	91	13.326
4.022	6.986	90	13.196
4.852	8.494	84	12.410
1.822	3.163	81	11.949
8.816	15.197	93	13.641
7.872	13.164	88	12.950
2.531	4.451	84	12.384
3.595	6.722	96	14.121
3.261	5.348	84	12.326
2.702	4.953	90	13.197
2.613	4.482	90	13.232
1.747	3.131	90	13.190
6.816	12.115	85	12.550
2.631	4.741	87	12.772
1.586	2.831	76	11.231
4.831	8.586	101	14.830
14.237	24.686	89	13.061
3.447	6.316	110	16.146
8.178	14.680	106	15.568
3.671	6.804	104	15.311
4.194	7.536	103	15.095
5.132	9.460	92	13.511
12.580	22.252	110	16.091
3.578	6.503	102	14.943
10.006	18.109	94	13.848
4.502	8.428	113	16.629
6.730	12.135	93	13.637
64.771	107.796	100	14.749
2.453	4.387	93	13.602
6.369	11.462	104	15.350
15.968	27.083	89	13.096
4.247	7.766	100	14.720
2.579	4.601	84	12.411
7.872	13.512	80	11.793
1.640	2.913	84	12.307
6.160	10.853	91	13.376
4.989	8.554	88	12.870
3.493	5.743	79	11.667
9.952	17.728	98	14.428




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=116587&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=116587&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116587&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 time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.







Correlations for all pairs of data series (method=kendall)
Totaalinwonerswelvaartgem_ink
Totaal10.950.0790.078
inwoners0.9510.0950.094
welvaart0.0790.09510.99
gem_ink 0.0780.0940.991

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Totaal & inwoners & welvaart & gem_ink
 \tabularnewline
Totaal & 1 & 0.95 & 0.079 & 0.078 \tabularnewline
inwoners & 0.95 & 1 & 0.095 & 0.094 \tabularnewline
welvaart & 0.079 & 0.095 & 1 & 0.99 \tabularnewline
gem_ink
 & 0.078 & 0.094 & 0.99 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116587&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Totaal[/C][C]inwoners[/C][C]welvaart[/C][C]gem_ink
[/C][/ROW]
[ROW][C]Totaal[/C][C]1[/C][C]0.95[/C][C]0.079[/C][C]0.078[/C][/ROW]
[ROW][C]inwoners[/C][C]0.95[/C][C]1[/C][C]0.095[/C][C]0.094[/C][/ROW]
[ROW][C]welvaart[/C][C]0.079[/C][C]0.095[/C][C]1[/C][C]0.99[/C][/ROW]
[ROW][C]gem_ink
[/C][C]0.078[/C][C]0.094[/C][C]0.99[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116587&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116587&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)
Totaalinwonerswelvaartgem_ink
Totaal10.950.0790.078
inwoners0.9510.0950.094
welvaart0.0790.09510.99
gem_ink 0.0780.0940.991







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Totaal;inwoners0.40180.9680.95
p-value(0)(0)(0)
Totaal;welvaart-0.09830.1140.0794
p-value(0.017)(0.0056)(0.0044)
Totaal;gem_ink -0.09960.11340.0783
p-value(0.0156)(0.0059)(0.0045)
inwoners;welvaart-0.09640.13660.0952
p-value(0.0193)(9e-04)(6e-04)
inwoners;gem_ink -0.09630.13610.0941
p-value(0.0194)(9e-04)(6e-04)
welvaart;gem_ink 0.99980.99970.9897
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
Totaal;inwoners & 0.4018 & 0.968 & 0.95 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Totaal;welvaart & -0.0983 & 0.114 & 0.0794 \tabularnewline
p-value & (0.017) & (0.0056) & (0.0044) \tabularnewline
Totaal;gem_ink
 & -0.0996 & 0.1134 & 0.0783 \tabularnewline
p-value & (0.0156) & (0.0059) & (0.0045) \tabularnewline
inwoners;welvaart & -0.0964 & 0.1366 & 0.0952 \tabularnewline
p-value & (0.0193) & (9e-04) & (6e-04) \tabularnewline
inwoners;gem_ink
 & -0.0963 & 0.1361 & 0.0941 \tabularnewline
p-value & (0.0194) & (9e-04) & (6e-04) \tabularnewline
welvaart;gem_ink
 & 0.9998 & 0.9997 & 0.9897 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116587&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]Totaal;inwoners[/C][C]0.4018[/C][C]0.968[/C][C]0.95[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Totaal;welvaart[/C][C]-0.0983[/C][C]0.114[/C][C]0.0794[/C][/ROW]
[ROW][C]p-value[/C][C](0.017)[/C][C](0.0056)[/C][C](0.0044)[/C][/ROW]
[ROW][C]Totaal;gem_ink
[/C][C]-0.0996[/C][C]0.1134[/C][C]0.0783[/C][/ROW]
[ROW][C]p-value[/C][C](0.0156)[/C][C](0.0059)[/C][C](0.0045)[/C][/ROW]
[ROW][C]inwoners;welvaart[/C][C]-0.0964[/C][C]0.1366[/C][C]0.0952[/C][/ROW]
[ROW][C]p-value[/C][C](0.0193)[/C][C](9e-04)[/C][C](6e-04)[/C][/ROW]
[ROW][C]inwoners;gem_ink
[/C][C]-0.0963[/C][C]0.1361[/C][C]0.0941[/C][/ROW]
[ROW][C]p-value[/C][C](0.0194)[/C][C](9e-04)[/C][C](6e-04)[/C][/ROW]
[ROW][C]welvaart;gem_ink
[/C][C]0.9998[/C][C]0.9997[/C][C]0.9897[/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=116587&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116587&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
Totaal;inwoners0.40180.9680.95
p-value(0)(0)(0)
Totaal;welvaart-0.09830.1140.0794
p-value(0.017)(0.0056)(0.0044)
Totaal;gem_ink -0.09960.11340.0783
p-value(0.0156)(0.0059)(0.0045)
inwoners;welvaart-0.09640.13660.0952
p-value(0.0193)(9e-04)(6e-04)
inwoners;gem_ink -0.09630.13610.0941
p-value(0.0194)(9e-04)(6e-04)
welvaart;gem_ink 0.99980.99970.9897
p-value(0)(0)(0)



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')