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Author's title

Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 13 Dec 2010 15:59:58 +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/13/t1292255878nppl3o2hqr6lv4m.htm/, Retrieved Mon, 06 May 2024 19:42:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108966, Retrieved Mon, 06 May 2024 19:42:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
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]
F   PD  [Kendall tau Correlation Matrix] [Pearson Correlati...] [2010-12-13 15:38:41] [2843717cd92615903379c14ebee3c5df]
F   P       [Kendall tau Correlation Matrix] [Kendall's tau Cor...] [2010-12-13 15:59:58] [dfb0309aec67f282200eef05efe0d5bd] [Current]
Feedback Forum
2010-12-18 10:21:05 [00c625c7d009d84797af914265b614f9] [reply
Correct,
Dit is hier beter voor het bekijken van de correlatie want hier wordt niet uitgegaan van de normaliteits assumpties.

Post a new message
Dataseries X:
0	13	26	9	6	25	25
0	16	20	9	6	25	24
0	19	21	9	13	19	21
1	15	31	14	8	18	23
0	14	21	8	7	18	17
0	13	18	8	9	22	19
0	19	26	11	5	29	18
0	15	22	10	8	26	27
0	14	22	9	9	25	23
0	15	29	15	11	23	23
1	16	15	14	8	23	29
0	16	16	11	11	23	21
1	16	24	14	12	24	26
0	17	17	6	8	30	25
1	15	19	20	7	19	25
1	15	22	9	9	24	23
0	20	31	10	12	32	26
1	18	28	8	20	30	20
0	16	38	11	7	29	29
1	16	26	14	8	17	24
0	19	25	11	8	25	23
0	16	25	16	16	26	24
1	17	29	14	10	26	30
0	17	28	11	6	25	22
1	16	15	11	8	23	22
0	15	18	12	9	21	13
1	14	21	9	9	19	24
0	15	25	7	11	35	17
1	12	23	13	12	19	24
0	14	23	10	8	20	21
0	16	19	9	7	21	23
1	14	18	9	8	21	24
1	7	18	13	9	24	24
1	10	26	16	4	23	24
1	14	18	12	8	19	23
0	16	18	6	8	17	26
1	16	28	14	8	24	24
1	16	17	14	6	15	21
0	14	29	10	8	25	23
1	20	12	4	4	27	28
1	14	25	12	7	29	23
0	14	28	12	14	27	22
0	11	20	14	10	18	24
0	15	17	9	9	25	21
0	16	17	9	6	22	23
1	14	20	10	8	26	23
0	16	31	14	11	23	20
1	14	21	10	8	16	23
1	12	19	9	8	27	21
0	16	23	14	10	25	27
1	9	15	8	8	14	12
0	14	24	9	10	19	15
0	16	28	8	7	20	22
0	16	16	9	8	16	21
1	15	19	9	7	18	21
0	16	21	9	9	22	20
1	12	21	15	5	21	24
1	16	20	8	7	22	24
0	16	16	10	7	22	29
0	14	25	8	7	32	25
0	16	30	14	9	23	14
1	17	29	11	5	31	30
0	18	22	10	8	18	19
1	18	19	12	8	23	29
0	12	33	14	8	26	25
1	16	17	9	9	24	25
1	10	9	13	6	19	25
0	14	14	15	8	14	16
0	18	15	8	6	20	25
1	18	12	7	4	22	28
1	16	21	10	6	24	24
0	16	20	10	4	25	25
0	16	29	13	12	21	21
1	13	33	11	6	28	22
1	16	21	8	11	24	20
1	16	15	12	8	20	25
1	20	19	9	10	21	27
0	16	23	10	10	23	21
1	15	20	11	4	13	13
0	15	20	11	8	24	26
0	16	18	10	9	21	26
1	14	31	16	9	21	25
0	15	18	16	7	17	22
0	12	13	8	7	14	19
0	17	9	6	11	29	23
0	16	20	11	8	25	25
0	15	18	12	8	16	15
0	13	23	14	7	25	21
0	16	17	9	5	25	23
0	16	17	11	7	21	25
0	16	16	8	9	23	24
1	16	31	8	8	22	24
1	14	15	7	6	19	21
0	16	28	16	8	24	24
1	16	26	13	10	26	22
0	20	20	8	10	25	24
1	15	19	11	8	20	28
0	16	25	14	11	22	21
1	13	18	10	8	14	17
0	17	20	10	8	20	28
1	16	33	14	6	32	24
0	12	24	14	20	21	10
0	16	22	10	6	22	20
0	16	32	12	12	28	22
0	17	31	9	9	25	19
1	13	13	16	5	17	22
0	12	18	8	10	21	22
1	18	17	9	5	23	26
0	14	29	16	6	27	24
0	14	22	13	10	22	22
0	13	18	13	6	19	20
0	16	22	8	10	20	20
0	13	25	14	5	17	15
0	16	20	11	13	24	20
0	13	20	9	7	21	20
0	16	17	8	9	21	24
0	15	21	13	11	23	22
0	16	26	13	8	24	29
1	15	10	10	5	19	23
0	17	15	8	4	22	24
0	15	20	7	9	26	22
0	12	14	11	7	17	16
1	16	16	11	5	17	23
1	10	23	14	5	19	27
0	16	11	6	4	15	16
1	14	19	10	7	17	21
0	15	30	9	9	27	26
1	13	21	12	8	19	22
1	15	20	11	8	21	23
0	11	22	14	11	25	19
0	12	30	12	10	19	18
1	8	25	14	9	22	24
0	16	28	8	12	18	24
1	15	23	14	10	20	29
0	17	23	8	10	15	22
1	16	21	11	7	20	24
0	10	30	12	10	29	22
0	18	22	9	6	19	12
1	13	32	16	6	29	26
0	15	22	11	11	24	18
1	16	15	11	8	23	22
0	16	21	12	9	22	24
0	14	27	15	9	23	21
0	10	22	13	13	22	15
0	17	9	6	11	29	23
0	13	29	11	4	26	22
0	15	20	7	9	26	22
0	16	16	8	5	21	24
0	12	16	8	4	18	23
0	13	16	9	9	10	13




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108966&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108966&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108966&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'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=kendall)
GenderLearningConcernDoubtsCriticismStandardsOrganization
Gender1-0.082-0.0790.15-0.193-0.1010.238
Learning-0.0821-0.042-0.2240.0360.1580.197
Concern-0.079-0.04210.2910.2050.2990.014
Doubts0.15-0.2240.29110.046-0.0040.057
Criticism-0.1930.0360.2050.04610.127-0.121
Standards-0.1010.1580.299-0.0040.12710.21
Organization0.2380.1970.0140.057-0.1210.211

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Gender & Learning & Concern & Doubts & Criticism & Standards & Organization \tabularnewline
Gender & 1 & -0.082 & -0.079 & 0.15 & -0.193 & -0.101 & 0.238 \tabularnewline
Learning & -0.082 & 1 & -0.042 & -0.224 & 0.036 & 0.158 & 0.197 \tabularnewline
Concern & -0.079 & -0.042 & 1 & 0.291 & 0.205 & 0.299 & 0.014 \tabularnewline
Doubts & 0.15 & -0.224 & 0.291 & 1 & 0.046 & -0.004 & 0.057 \tabularnewline
Criticism & -0.193 & 0.036 & 0.205 & 0.046 & 1 & 0.127 & -0.121 \tabularnewline
Standards & -0.101 & 0.158 & 0.299 & -0.004 & 0.127 & 1 & 0.21 \tabularnewline
Organization & 0.238 & 0.197 & 0.014 & 0.057 & -0.121 & 0.21 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108966&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]Learning[/C][C]Concern[/C][C]Doubts[/C][C]Criticism[/C][C]Standards[/C][C]Organization[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]-0.082[/C][C]-0.079[/C][C]0.15[/C][C]-0.193[/C][C]-0.101[/C][C]0.238[/C][/ROW]
[ROW][C]Learning[/C][C]-0.082[/C][C]1[/C][C]-0.042[/C][C]-0.224[/C][C]0.036[/C][C]0.158[/C][C]0.197[/C][/ROW]
[ROW][C]Concern[/C][C]-0.079[/C][C]-0.042[/C][C]1[/C][C]0.291[/C][C]0.205[/C][C]0.299[/C][C]0.014[/C][/ROW]
[ROW][C]Doubts[/C][C]0.15[/C][C]-0.224[/C][C]0.291[/C][C]1[/C][C]0.046[/C][C]-0.004[/C][C]0.057[/C][/ROW]
[ROW][C]Criticism[/C][C]-0.193[/C][C]0.036[/C][C]0.205[/C][C]0.046[/C][C]1[/C][C]0.127[/C][C]-0.121[/C][/ROW]
[ROW][C]Standards[/C][C]-0.101[/C][C]0.158[/C][C]0.299[/C][C]-0.004[/C][C]0.127[/C][C]1[/C][C]0.21[/C][/ROW]
[ROW][C]Organization[/C][C]0.238[/C][C]0.197[/C][C]0.014[/C][C]0.057[/C][C]-0.121[/C][C]0.21[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108966&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108966&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)
GenderLearningConcernDoubtsCriticismStandardsOrganization
Gender1-0.082-0.0790.15-0.193-0.1010.238
Learning-0.0821-0.042-0.2240.0360.1580.197
Concern-0.079-0.04210.2910.2050.2990.014
Doubts0.15-0.2240.29110.046-0.0040.057
Criticism-0.1930.0360.2050.04610.127-0.121
Standards-0.1010.1580.299-0.0040.12710.21
Organization0.2380.1970.0140.057-0.1210.211







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Gender;Learning-0.1135-0.0939-0.0825
p-value(0.1667)(0.2532)(0.2519)
Gender;Concern-0.0868-0.0936-0.0785
p-value(0.2907)(0.2546)(0.2533)
Gender;Doubts0.17240.1740.1498
p-value(0.0349)(0.0332)(0.0337)
Gender;Criticism-0.1884-0.2233-0.1932
p-value(0.0209)(0.006)(0.0064)
Gender;Standards-0.1004-0.1198-0.1011
p-value(0.2215)(0.1443)(0.1437)
Gender;Organization0.26880.2790.2378
p-value(9e-04)(5e-04)(7e-04)
Learning;Concern-0.019-0.0502-0.0424
p-value(0.8177)(0.5419)(0.4825)
Learning;Doubts-0.318-0.2973-0.2245
p-value(1e-04)(2e-04)(3e-04)
Learning;Criticism0.03190.040.036
p-value(0.6983)(0.6266)(0.5637)
Learning;Standards0.20840.21430.1581
p-value(0.0105)(0.0085)(0.0093)
Learning;Organization0.24760.25760.1969
p-value(0.0023)(0.0015)(0.0013)
Concern;Doubts0.37560.38440.2911
p-value(0)(0)(0)
Concern;Criticism0.24180.26780.2048
p-value(0.0029)(9e-04)(6e-04)
Concern;Standards0.41680.40440.2986
p-value(0)(0)(0)
Concern;Organization0.06870.02280.0136
p-value(0.4034)(0.7819)(0.816)
Doubts;Criticism0.08830.06440.0455
p-value(0.2824)(0.4333)(0.4562)
Doubts;Standards-0.0438-0.0069-0.0042
p-value(0.5943)(0.9334)(0.9437)
Doubts;Organization0.05670.07840.0566
p-value(0.4909)(0.3402)(0.3468)
Criticism;Standards0.18090.17050.1271
p-value(0.0268)(0.037)(0.0339)
Criticism;Organization-0.1833-0.1634-0.1208
p-value(0.0248)(0.0457)(0.0459)
Standards;Organization0.35550.29030.2101
p-value(0)(3e-04)(4e-04)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Gender;Learning & -0.1135 & -0.0939 & -0.0825 \tabularnewline
p-value & (0.1667) & (0.2532) & (0.2519) \tabularnewline
Gender;Concern & -0.0868 & -0.0936 & -0.0785 \tabularnewline
p-value & (0.2907) & (0.2546) & (0.2533) \tabularnewline
Gender;Doubts & 0.1724 & 0.174 & 0.1498 \tabularnewline
p-value & (0.0349) & (0.0332) & (0.0337) \tabularnewline
Gender;Criticism & -0.1884 & -0.2233 & -0.1932 \tabularnewline
p-value & (0.0209) & (0.006) & (0.0064) \tabularnewline
Gender;Standards & -0.1004 & -0.1198 & -0.1011 \tabularnewline
p-value & (0.2215) & (0.1443) & (0.1437) \tabularnewline
Gender;Organization & 0.2688 & 0.279 & 0.2378 \tabularnewline
p-value & (9e-04) & (5e-04) & (7e-04) \tabularnewline
Learning;Concern & -0.019 & -0.0502 & -0.0424 \tabularnewline
p-value & (0.8177) & (0.5419) & (0.4825) \tabularnewline
Learning;Doubts & -0.318 & -0.2973 & -0.2245 \tabularnewline
p-value & (1e-04) & (2e-04) & (3e-04) \tabularnewline
Learning;Criticism & 0.0319 & 0.04 & 0.036 \tabularnewline
p-value & (0.6983) & (0.6266) & (0.5637) \tabularnewline
Learning;Standards & 0.2084 & 0.2143 & 0.1581 \tabularnewline
p-value & (0.0105) & (0.0085) & (0.0093) \tabularnewline
Learning;Organization & 0.2476 & 0.2576 & 0.1969 \tabularnewline
p-value & (0.0023) & (0.0015) & (0.0013) \tabularnewline
Concern;Doubts & 0.3756 & 0.3844 & 0.2911 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Concern;Criticism & 0.2418 & 0.2678 & 0.2048 \tabularnewline
p-value & (0.0029) & (9e-04) & (6e-04) \tabularnewline
Concern;Standards & 0.4168 & 0.4044 & 0.2986 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Concern;Organization & 0.0687 & 0.0228 & 0.0136 \tabularnewline
p-value & (0.4034) & (0.7819) & (0.816) \tabularnewline
Doubts;Criticism & 0.0883 & 0.0644 & 0.0455 \tabularnewline
p-value & (0.2824) & (0.4333) & (0.4562) \tabularnewline
Doubts;Standards & -0.0438 & -0.0069 & -0.0042 \tabularnewline
p-value & (0.5943) & (0.9334) & (0.9437) \tabularnewline
Doubts;Organization & 0.0567 & 0.0784 & 0.0566 \tabularnewline
p-value & (0.4909) & (0.3402) & (0.3468) \tabularnewline
Criticism;Standards & 0.1809 & 0.1705 & 0.1271 \tabularnewline
p-value & (0.0268) & (0.037) & (0.0339) \tabularnewline
Criticism;Organization & -0.1833 & -0.1634 & -0.1208 \tabularnewline
p-value & (0.0248) & (0.0457) & (0.0459) \tabularnewline
Standards;Organization & 0.3555 & 0.2903 & 0.2101 \tabularnewline
p-value & (0) & (3e-04) & (4e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108966&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]Gender;Learning[/C][C]-0.1135[/C][C]-0.0939[/C][C]-0.0825[/C][/ROW]
[ROW][C]p-value[/C][C](0.1667)[/C][C](0.2532)[/C][C](0.2519)[/C][/ROW]
[ROW][C]Gender;Concern[/C][C]-0.0868[/C][C]-0.0936[/C][C]-0.0785[/C][/ROW]
[ROW][C]p-value[/C][C](0.2907)[/C][C](0.2546)[/C][C](0.2533)[/C][/ROW]
[ROW][C]Gender;Doubts[/C][C]0.1724[/C][C]0.174[/C][C]0.1498[/C][/ROW]
[ROW][C]p-value[/C][C](0.0349)[/C][C](0.0332)[/C][C](0.0337)[/C][/ROW]
[ROW][C]Gender;Criticism[/C][C]-0.1884[/C][C]-0.2233[/C][C]-0.1932[/C][/ROW]
[ROW][C]p-value[/C][C](0.0209)[/C][C](0.006)[/C][C](0.0064)[/C][/ROW]
[ROW][C]Gender;Standards[/C][C]-0.1004[/C][C]-0.1198[/C][C]-0.1011[/C][/ROW]
[ROW][C]p-value[/C][C](0.2215)[/C][C](0.1443)[/C][C](0.1437)[/C][/ROW]
[ROW][C]Gender;Organization[/C][C]0.2688[/C][C]0.279[/C][C]0.2378[/C][/ROW]
[ROW][C]p-value[/C][C](9e-04)[/C][C](5e-04)[/C][C](7e-04)[/C][/ROW]
[ROW][C]Learning;Concern[/C][C]-0.019[/C][C]-0.0502[/C][C]-0.0424[/C][/ROW]
[ROW][C]p-value[/C][C](0.8177)[/C][C](0.5419)[/C][C](0.4825)[/C][/ROW]
[ROW][C]Learning;Doubts[/C][C]-0.318[/C][C]-0.2973[/C][C]-0.2245[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](2e-04)[/C][C](3e-04)[/C][/ROW]
[ROW][C]Learning;Criticism[/C][C]0.0319[/C][C]0.04[/C][C]0.036[/C][/ROW]
[ROW][C]p-value[/C][C](0.6983)[/C][C](0.6266)[/C][C](0.5637)[/C][/ROW]
[ROW][C]Learning;Standards[/C][C]0.2084[/C][C]0.2143[/C][C]0.1581[/C][/ROW]
[ROW][C]p-value[/C][C](0.0105)[/C][C](0.0085)[/C][C](0.0093)[/C][/ROW]
[ROW][C]Learning;Organization[/C][C]0.2476[/C][C]0.2576[/C][C]0.1969[/C][/ROW]
[ROW][C]p-value[/C][C](0.0023)[/C][C](0.0015)[/C][C](0.0013)[/C][/ROW]
[ROW][C]Concern;Doubts[/C][C]0.3756[/C][C]0.3844[/C][C]0.2911[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Concern;Criticism[/C][C]0.2418[/C][C]0.2678[/C][C]0.2048[/C][/ROW]
[ROW][C]p-value[/C][C](0.0029)[/C][C](9e-04)[/C][C](6e-04)[/C][/ROW]
[ROW][C]Concern;Standards[/C][C]0.4168[/C][C]0.4044[/C][C]0.2986[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Concern;Organization[/C][C]0.0687[/C][C]0.0228[/C][C]0.0136[/C][/ROW]
[ROW][C]p-value[/C][C](0.4034)[/C][C](0.7819)[/C][C](0.816)[/C][/ROW]
[ROW][C]Doubts;Criticism[/C][C]0.0883[/C][C]0.0644[/C][C]0.0455[/C][/ROW]
[ROW][C]p-value[/C][C](0.2824)[/C][C](0.4333)[/C][C](0.4562)[/C][/ROW]
[ROW][C]Doubts;Standards[/C][C]-0.0438[/C][C]-0.0069[/C][C]-0.0042[/C][/ROW]
[ROW][C]p-value[/C][C](0.5943)[/C][C](0.9334)[/C][C](0.9437)[/C][/ROW]
[ROW][C]Doubts;Organization[/C][C]0.0567[/C][C]0.0784[/C][C]0.0566[/C][/ROW]
[ROW][C]p-value[/C][C](0.4909)[/C][C](0.3402)[/C][C](0.3468)[/C][/ROW]
[ROW][C]Criticism;Standards[/C][C]0.1809[/C][C]0.1705[/C][C]0.1271[/C][/ROW]
[ROW][C]p-value[/C][C](0.0268)[/C][C](0.037)[/C][C](0.0339)[/C][/ROW]
[ROW][C]Criticism;Organization[/C][C]-0.1833[/C][C]-0.1634[/C][C]-0.1208[/C][/ROW]
[ROW][C]p-value[/C][C](0.0248)[/C][C](0.0457)[/C][C](0.0459)[/C][/ROW]
[ROW][C]Standards;Organization[/C][C]0.3555[/C][C]0.2903[/C][C]0.2101[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](3e-04)[/C][C](4e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108966&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108966&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
Gender;Learning-0.1135-0.0939-0.0825
p-value(0.1667)(0.2532)(0.2519)
Gender;Concern-0.0868-0.0936-0.0785
p-value(0.2907)(0.2546)(0.2533)
Gender;Doubts0.17240.1740.1498
p-value(0.0349)(0.0332)(0.0337)
Gender;Criticism-0.1884-0.2233-0.1932
p-value(0.0209)(0.006)(0.0064)
Gender;Standards-0.1004-0.1198-0.1011
p-value(0.2215)(0.1443)(0.1437)
Gender;Organization0.26880.2790.2378
p-value(9e-04)(5e-04)(7e-04)
Learning;Concern-0.019-0.0502-0.0424
p-value(0.8177)(0.5419)(0.4825)
Learning;Doubts-0.318-0.2973-0.2245
p-value(1e-04)(2e-04)(3e-04)
Learning;Criticism0.03190.040.036
p-value(0.6983)(0.6266)(0.5637)
Learning;Standards0.20840.21430.1581
p-value(0.0105)(0.0085)(0.0093)
Learning;Organization0.24760.25760.1969
p-value(0.0023)(0.0015)(0.0013)
Concern;Doubts0.37560.38440.2911
p-value(0)(0)(0)
Concern;Criticism0.24180.26780.2048
p-value(0.0029)(9e-04)(6e-04)
Concern;Standards0.41680.40440.2986
p-value(0)(0)(0)
Concern;Organization0.06870.02280.0136
p-value(0.4034)(0.7819)(0.816)
Doubts;Criticism0.08830.06440.0455
p-value(0.2824)(0.4333)(0.4562)
Doubts;Standards-0.0438-0.0069-0.0042
p-value(0.5943)(0.9334)(0.9437)
Doubts;Organization0.05670.07840.0566
p-value(0.4909)(0.3402)(0.3468)
Criticism;Standards0.18090.17050.1271
p-value(0.0268)(0.037)(0.0339)
Criticism;Organization-0.1833-0.1634-0.1208
p-value(0.0248)(0.0457)(0.0459)
Standards;Organization0.35550.29030.2101
p-value(0)(3e-04)(4e-04)



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')