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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 20 Dec 2011 20:33:01 -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/2011/Dec/20/t1324431210o00mr4kaig7j8cx.htm/, Retrieved Sun, 05 May 2024 23:58:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158343, Retrieved Sun, 05 May 2024 23:58:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [paper] [2011-12-21 01:33:01] [6e647d331a8f33aa61a2d78ef323178e] [Current]
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Dataseries X:
2	210907	56	396	79	30	1	0
0	149061	44	656	43	26	1	0
0	237213	84	655	78	38	1	1
4	133131	55	525	44	30	1	1
0	324799	154	1436	158	47	1	1
0	230964	53	612	102	30	1	0
0	236785	119	865	77	31	1	1
1	344297	75	963	80	30	1	1
0	174724	92	966	123	34	1	1
3	174415	100	801	73	31	1	1
0	223632	73	513	105	33	1	1
4	294424	77	992	107	33	1	0
1	106408	30	260	33	14	1	0
0	96560	76	503	42	17	0	0
0	265769	146	927	96	32	1	1
0	149112	56	537	56	35	1	0
2	152871	58	532	59	28	1	0
2	362301	119	1635	76	34	1	1
0	183167	66	557	91	39	1	0
2	218946	41	866	76	29	1	1
2	244052	68	574	101	44	1	1
0	341570	168	1276	94	21	0	1
0	196553	57	503	41	29	1	1
2	143246	103	464	67	27	1	0
0	167488	45	619	69	28	1	0
4	143756	46	479	105	34	1	0
2	152299	53	537	62	33	1	1
2	193339	78	465	100	35	1	1
0	130585	46	299	67	29	1	0
3	112611	41	248	46	20	0	1
3	148446	91	905	135	37	1	1
2	182079	63	512	124	33	1	0
0	243060	63	786	58	29	1	1
0	162765	32	489	68	28	1	1
0	85574	34	351	37	21	0	1
1	225060	93	669	93	41	1	0
0	133328	55	506	56	20	0	1
3	100750	72	407	83	30	1	1
0	101523	42	316	59	22	0	1
0	243511	71	603	133	42	1	1
0	152474	65	577	106	32	1	1
3	132487	41	411	71	36	1	1
0	317394	86	975	116	31	1	0
0	244749	95	964	98	33	1	1
2	128423	64	369	32	38	1	0
0	97839	38	417	25	24	1	0
2	229242	247	719	63	31	1	1
2	324598	110	1402	113	37	1	0
0	195838	67	564	111	31	1	0
0	254488	83	747	120	39	1	0
0	92499	32	319	25	18	0	1
0	224330	83	612	131	39	1	0
6	181633	70	564	47	30	1	1
0	271856	103	824	109	37	1	1
3	95227	34	239	37	32	1	1
0	98146	40	459	15	17	0	0
0	118612	46	454	54	12	0	0
1	65475	18	225	16	13	0	1
0	108446	60	389	22	17	0	0
2	121848	39	339	37	17	0	0
2	76302	31	333	29	20	0	1
0	98104	54	636	55	17	0	0
0	30989	14	93	5	17	0	1
1	31774	23	170	0	17	0	0
0	150580	77	530	27	22	0	1
1	59382	49	227	29	12	0	0
0	84105	20	261	17	17	0	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158343&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158343&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158343&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=pearson)
TestscoreRFC_timeLoginsCviewsBcompCompRevCourseIdGeslacht
Testscore1-0.0350.008-0.0220.0030.1680.2370.117
RFC_time-0.03510.6680.8630.7160.6430.5520.158
Logins0.0080.66810.690.5110.4450.3310.219
Cviews-0.0220.8630.6910.6320.5090.4060.18
Bcomp0.0030.7160.5110.63210.7710.6130.077
CompRev0.1680.6430.4450.5090.77110.8120.166
CourseId0.2370.5520.3310.4060.6130.81210.033
Geslacht0.1170.1580.2190.180.0770.1660.0331

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Testscore & RFC_time & Logins & Cviews & Bcomp & CompRev & CourseId & Geslacht \tabularnewline
Testscore & 1 & -0.035 & 0.008 & -0.022 & 0.003 & 0.168 & 0.237 & 0.117 \tabularnewline
RFC_time & -0.035 & 1 & 0.668 & 0.863 & 0.716 & 0.643 & 0.552 & 0.158 \tabularnewline
Logins & 0.008 & 0.668 & 1 & 0.69 & 0.511 & 0.445 & 0.331 & 0.219 \tabularnewline
Cviews & -0.022 & 0.863 & 0.69 & 1 & 0.632 & 0.509 & 0.406 & 0.18 \tabularnewline
Bcomp & 0.003 & 0.716 & 0.511 & 0.632 & 1 & 0.771 & 0.613 & 0.077 \tabularnewline
CompRev & 0.168 & 0.643 & 0.445 & 0.509 & 0.771 & 1 & 0.812 & 0.166 \tabularnewline
CourseId & 0.237 & 0.552 & 0.331 & 0.406 & 0.613 & 0.812 & 1 & 0.033 \tabularnewline
Geslacht & 0.117 & 0.158 & 0.219 & 0.18 & 0.077 & 0.166 & 0.033 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158343&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Testscore[/C][C]RFC_time[/C][C]Logins[/C][C]Cviews[/C][C]Bcomp[/C][C]CompRev[/C][C]CourseId[/C][C]Geslacht[/C][/ROW]
[ROW][C]Testscore[/C][C]1[/C][C]-0.035[/C][C]0.008[/C][C]-0.022[/C][C]0.003[/C][C]0.168[/C][C]0.237[/C][C]0.117[/C][/ROW]
[ROW][C]RFC_time[/C][C]-0.035[/C][C]1[/C][C]0.668[/C][C]0.863[/C][C]0.716[/C][C]0.643[/C][C]0.552[/C][C]0.158[/C][/ROW]
[ROW][C]Logins[/C][C]0.008[/C][C]0.668[/C][C]1[/C][C]0.69[/C][C]0.511[/C][C]0.445[/C][C]0.331[/C][C]0.219[/C][/ROW]
[ROW][C]Cviews[/C][C]-0.022[/C][C]0.863[/C][C]0.69[/C][C]1[/C][C]0.632[/C][C]0.509[/C][C]0.406[/C][C]0.18[/C][/ROW]
[ROW][C]Bcomp[/C][C]0.003[/C][C]0.716[/C][C]0.511[/C][C]0.632[/C][C]1[/C][C]0.771[/C][C]0.613[/C][C]0.077[/C][/ROW]
[ROW][C]CompRev[/C][C]0.168[/C][C]0.643[/C][C]0.445[/C][C]0.509[/C][C]0.771[/C][C]1[/C][C]0.812[/C][C]0.166[/C][/ROW]
[ROW][C]CourseId[/C][C]0.237[/C][C]0.552[/C][C]0.331[/C][C]0.406[/C][C]0.613[/C][C]0.812[/C][C]1[/C][C]0.033[/C][/ROW]
[ROW][C]Geslacht[/C][C]0.117[/C][C]0.158[/C][C]0.219[/C][C]0.18[/C][C]0.077[/C][C]0.166[/C][C]0.033[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158343&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158343&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)
TestscoreRFC_timeLoginsCviewsBcompCompRevCourseIdGeslacht
Testscore1-0.0350.008-0.0220.0030.1680.2370.117
RFC_time-0.03510.6680.8630.7160.6430.5520.158
Logins0.0080.66810.690.5110.4450.3310.219
Cviews-0.0220.8630.6910.6320.5090.4060.18
Bcomp0.0030.7160.5110.63210.7710.6130.077
CompRev0.1680.6430.4450.5090.77110.8120.166
CourseId0.2370.5520.3310.4060.6130.81210.033
Geslacht0.1170.1580.2190.180.0770.1660.0331







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Testscore;RFC_time-0.0347-0.0684-0.0525
p-value(0.7802)(0.5826)(0.5777)
Testscore;Logins0.0079-0.0072-0.004
p-value(0.9494)(0.9537)(0.9666)
Testscore;Cviews-0.022-0.1062-0.0728
p-value(0.8597)(0.3923)(0.44)
Testscore;Bcomp0.00340.01120.0113
p-value(0.9783)(0.9281)(0.9047)
Testscore;CompRev0.16820.15210.1101
p-value(0.1736)(0.219)(0.2519)
Testscore;CourseId0.2370.21920.2038
p-value(0.0534)(0.0747)(0.075)
Testscore;Geslacht0.11650.08820.082
p-value(0.3476)(0.4778)(0.4736)
RFC_time;Logins0.6680.76320.5878
p-value(0)(0)(0)
RFC_time;Cviews0.86310.85580.6867
p-value(0)(0)(0)
RFC_time;Bcomp0.71640.76670.5753
p-value(0)(0)(0)
RFC_time;CompRev0.64330.67270.493
p-value(0)(0)(0)
RFC_time;CourseId0.55240.6250.5141
p-value(0)(0)(0)
RFC_time;Geslacht0.15770.1630.134
p-value(0.2026)(0.1876)(0.1855)
Logins;Cviews0.690.77610.5893
p-value(0)(0)(0)
Logins;Bcomp0.51110.67390.4741
p-value(0)(0)(0)
Logins;CompRev0.44450.60880.4423
p-value(2e-04)(0)(0)
Logins;CourseId0.33110.45550.376
p-value(0.0062)(1e-04)(2e-04)
Logins;Geslacht0.21940.15990.132
p-value(0.0744)(0.1962)(0.194)
Cviews;Bcomp0.63180.69990.5113
p-value(0)(0)(0)
Cviews;CompRev0.50850.56960.4083
p-value(0)(0)(0)
Cviews;CourseId0.40580.51970.4278
p-value(7e-04)(0)(0)
Cviews;Geslacht0.17950.15440.1271
p-value(0.1461)(0.2121)(0.2096)
Bcomp;CompRev0.77060.76950.5969
p-value(0)(0)(0)
Bcomp;CourseId0.6130.63450.523
p-value(0)(0)(0)
Bcomp;Geslacht0.07730.07680.0633
p-value(0.534)(0.5366)(0.5325)
CompRev;CourseId0.81160.75490.633
p-value(0)(0)(0)
CompRev;Geslacht0.16620.1540.1291
p-value(0.179)(0.2135)(0.211)
CourseId;Geslacht0.03280.03280.0328
p-value(0.7922)(0.7922)(0.7899)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Testscore;RFC_time & -0.0347 & -0.0684 & -0.0525 \tabularnewline
p-value & (0.7802) & (0.5826) & (0.5777) \tabularnewline
Testscore;Logins & 0.0079 & -0.0072 & -0.004 \tabularnewline
p-value & (0.9494) & (0.9537) & (0.9666) \tabularnewline
Testscore;Cviews & -0.022 & -0.1062 & -0.0728 \tabularnewline
p-value & (0.8597) & (0.3923) & (0.44) \tabularnewline
Testscore;Bcomp & 0.0034 & 0.0112 & 0.0113 \tabularnewline
p-value & (0.9783) & (0.9281) & (0.9047) \tabularnewline
Testscore;CompRev & 0.1682 & 0.1521 & 0.1101 \tabularnewline
p-value & (0.1736) & (0.219) & (0.2519) \tabularnewline
Testscore;CourseId & 0.237 & 0.2192 & 0.2038 \tabularnewline
p-value & (0.0534) & (0.0747) & (0.075) \tabularnewline
Testscore;Geslacht & 0.1165 & 0.0882 & 0.082 \tabularnewline
p-value & (0.3476) & (0.4778) & (0.4736) \tabularnewline
RFC_time;Logins & 0.668 & 0.7632 & 0.5878 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
RFC_time;Cviews & 0.8631 & 0.8558 & 0.6867 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
RFC_time;Bcomp & 0.7164 & 0.7667 & 0.5753 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
RFC_time;CompRev & 0.6433 & 0.6727 & 0.493 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
RFC_time;CourseId & 0.5524 & 0.625 & 0.5141 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
RFC_time;Geslacht & 0.1577 & 0.163 & 0.134 \tabularnewline
p-value & (0.2026) & (0.1876) & (0.1855) \tabularnewline
Logins;Cviews & 0.69 & 0.7761 & 0.5893 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Bcomp & 0.5111 & 0.6739 & 0.4741 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;CompRev & 0.4445 & 0.6088 & 0.4423 \tabularnewline
p-value & (2e-04) & (0) & (0) \tabularnewline
Logins;CourseId & 0.3311 & 0.4555 & 0.376 \tabularnewline
p-value & (0.0062) & (1e-04) & (2e-04) \tabularnewline
Logins;Geslacht & 0.2194 & 0.1599 & 0.132 \tabularnewline
p-value & (0.0744) & (0.1962) & (0.194) \tabularnewline
Cviews;Bcomp & 0.6318 & 0.6999 & 0.5113 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Cviews;CompRev & 0.5085 & 0.5696 & 0.4083 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Cviews;CourseId & 0.4058 & 0.5197 & 0.4278 \tabularnewline
p-value & (7e-04) & (0) & (0) \tabularnewline
Cviews;Geslacht & 0.1795 & 0.1544 & 0.1271 \tabularnewline
p-value & (0.1461) & (0.2121) & (0.2096) \tabularnewline
Bcomp;CompRev & 0.7706 & 0.7695 & 0.5969 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Bcomp;CourseId & 0.613 & 0.6345 & 0.523 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Bcomp;Geslacht & 0.0773 & 0.0768 & 0.0633 \tabularnewline
p-value & (0.534) & (0.5366) & (0.5325) \tabularnewline
CompRev;CourseId & 0.8116 & 0.7549 & 0.633 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CompRev;Geslacht & 0.1662 & 0.154 & 0.1291 \tabularnewline
p-value & (0.179) & (0.2135) & (0.211) \tabularnewline
CourseId;Geslacht & 0.0328 & 0.0328 & 0.0328 \tabularnewline
p-value & (0.7922) & (0.7922) & (0.7899) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158343&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]Testscore;RFC_time[/C][C]-0.0347[/C][C]-0.0684[/C][C]-0.0525[/C][/ROW]
[ROW][C]p-value[/C][C](0.7802)[/C][C](0.5826)[/C][C](0.5777)[/C][/ROW]
[ROW][C]Testscore;Logins[/C][C]0.0079[/C][C]-0.0072[/C][C]-0.004[/C][/ROW]
[ROW][C]p-value[/C][C](0.9494)[/C][C](0.9537)[/C][C](0.9666)[/C][/ROW]
[ROW][C]Testscore;Cviews[/C][C]-0.022[/C][C]-0.1062[/C][C]-0.0728[/C][/ROW]
[ROW][C]p-value[/C][C](0.8597)[/C][C](0.3923)[/C][C](0.44)[/C][/ROW]
[ROW][C]Testscore;Bcomp[/C][C]0.0034[/C][C]0.0112[/C][C]0.0113[/C][/ROW]
[ROW][C]p-value[/C][C](0.9783)[/C][C](0.9281)[/C][C](0.9047)[/C][/ROW]
[ROW][C]Testscore;CompRev[/C][C]0.1682[/C][C]0.1521[/C][C]0.1101[/C][/ROW]
[ROW][C]p-value[/C][C](0.1736)[/C][C](0.219)[/C][C](0.2519)[/C][/ROW]
[ROW][C]Testscore;CourseId[/C][C]0.237[/C][C]0.2192[/C][C]0.2038[/C][/ROW]
[ROW][C]p-value[/C][C](0.0534)[/C][C](0.0747)[/C][C](0.075)[/C][/ROW]
[ROW][C]Testscore;Geslacht[/C][C]0.1165[/C][C]0.0882[/C][C]0.082[/C][/ROW]
[ROW][C]p-value[/C][C](0.3476)[/C][C](0.4778)[/C][C](0.4736)[/C][/ROW]
[ROW][C]RFC_time;Logins[/C][C]0.668[/C][C]0.7632[/C][C]0.5878[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]RFC_time;Cviews[/C][C]0.8631[/C][C]0.8558[/C][C]0.6867[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]RFC_time;Bcomp[/C][C]0.7164[/C][C]0.7667[/C][C]0.5753[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]RFC_time;CompRev[/C][C]0.6433[/C][C]0.6727[/C][C]0.493[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]RFC_time;CourseId[/C][C]0.5524[/C][C]0.625[/C][C]0.5141[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]RFC_time;Geslacht[/C][C]0.1577[/C][C]0.163[/C][C]0.134[/C][/ROW]
[ROW][C]p-value[/C][C](0.2026)[/C][C](0.1876)[/C][C](0.1855)[/C][/ROW]
[ROW][C]Logins;Cviews[/C][C]0.69[/C][C]0.7761[/C][C]0.5893[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Bcomp[/C][C]0.5111[/C][C]0.6739[/C][C]0.4741[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;CompRev[/C][C]0.4445[/C][C]0.6088[/C][C]0.4423[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;CourseId[/C][C]0.3311[/C][C]0.4555[/C][C]0.376[/C][/ROW]
[ROW][C]p-value[/C][C](0.0062)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Logins;Geslacht[/C][C]0.2194[/C][C]0.1599[/C][C]0.132[/C][/ROW]
[ROW][C]p-value[/C][C](0.0744)[/C][C](0.1962)[/C][C](0.194)[/C][/ROW]
[ROW][C]Cviews;Bcomp[/C][C]0.6318[/C][C]0.6999[/C][C]0.5113[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Cviews;CompRev[/C][C]0.5085[/C][C]0.5696[/C][C]0.4083[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Cviews;CourseId[/C][C]0.4058[/C][C]0.5197[/C][C]0.4278[/C][/ROW]
[ROW][C]p-value[/C][C](7e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Cviews;Geslacht[/C][C]0.1795[/C][C]0.1544[/C][C]0.1271[/C][/ROW]
[ROW][C]p-value[/C][C](0.1461)[/C][C](0.2121)[/C][C](0.2096)[/C][/ROW]
[ROW][C]Bcomp;CompRev[/C][C]0.7706[/C][C]0.7695[/C][C]0.5969[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Bcomp;CourseId[/C][C]0.613[/C][C]0.6345[/C][C]0.523[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Bcomp;Geslacht[/C][C]0.0773[/C][C]0.0768[/C][C]0.0633[/C][/ROW]
[ROW][C]p-value[/C][C](0.534)[/C][C](0.5366)[/C][C](0.5325)[/C][/ROW]
[ROW][C]CompRev;CourseId[/C][C]0.8116[/C][C]0.7549[/C][C]0.633[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CompRev;Geslacht[/C][C]0.1662[/C][C]0.154[/C][C]0.1291[/C][/ROW]
[ROW][C]p-value[/C][C](0.179)[/C][C](0.2135)[/C][C](0.211)[/C][/ROW]
[ROW][C]CourseId;Geslacht[/C][C]0.0328[/C][C]0.0328[/C][C]0.0328[/C][/ROW]
[ROW][C]p-value[/C][C](0.7922)[/C][C](0.7922)[/C][C](0.7899)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158343&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158343&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
Testscore;RFC_time-0.0347-0.0684-0.0525
p-value(0.7802)(0.5826)(0.5777)
Testscore;Logins0.0079-0.0072-0.004
p-value(0.9494)(0.9537)(0.9666)
Testscore;Cviews-0.022-0.1062-0.0728
p-value(0.8597)(0.3923)(0.44)
Testscore;Bcomp0.00340.01120.0113
p-value(0.9783)(0.9281)(0.9047)
Testscore;CompRev0.16820.15210.1101
p-value(0.1736)(0.219)(0.2519)
Testscore;CourseId0.2370.21920.2038
p-value(0.0534)(0.0747)(0.075)
Testscore;Geslacht0.11650.08820.082
p-value(0.3476)(0.4778)(0.4736)
RFC_time;Logins0.6680.76320.5878
p-value(0)(0)(0)
RFC_time;Cviews0.86310.85580.6867
p-value(0)(0)(0)
RFC_time;Bcomp0.71640.76670.5753
p-value(0)(0)(0)
RFC_time;CompRev0.64330.67270.493
p-value(0)(0)(0)
RFC_time;CourseId0.55240.6250.5141
p-value(0)(0)(0)
RFC_time;Geslacht0.15770.1630.134
p-value(0.2026)(0.1876)(0.1855)
Logins;Cviews0.690.77610.5893
p-value(0)(0)(0)
Logins;Bcomp0.51110.67390.4741
p-value(0)(0)(0)
Logins;CompRev0.44450.60880.4423
p-value(2e-04)(0)(0)
Logins;CourseId0.33110.45550.376
p-value(0.0062)(1e-04)(2e-04)
Logins;Geslacht0.21940.15990.132
p-value(0.0744)(0.1962)(0.194)
Cviews;Bcomp0.63180.69990.5113
p-value(0)(0)(0)
Cviews;CompRev0.50850.56960.4083
p-value(0)(0)(0)
Cviews;CourseId0.40580.51970.4278
p-value(7e-04)(0)(0)
Cviews;Geslacht0.17950.15440.1271
p-value(0.1461)(0.2121)(0.2096)
Bcomp;CompRev0.77060.76950.5969
p-value(0)(0)(0)
Bcomp;CourseId0.6130.63450.523
p-value(0)(0)(0)
Bcomp;Geslacht0.07730.07680.0633
p-value(0.534)(0.5366)(0.5325)
CompRev;CourseId0.81160.75490.633
p-value(0)(0)(0)
CompRev;Geslacht0.16620.1540.1291
p-value(0.179)(0.2135)(0.211)
CourseId;Geslacht0.03280.03280.0328
p-value(0.7922)(0.7922)(0.7899)



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')