Free Statistics

of Irreproducible Research!

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 15:38:41 +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/t129225514674a197d92kw6q0m.htm/, Retrieved Tue, 07 May 2024 00:03:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108963, Retrieved Tue, 07 May 2024 00:03:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
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] [dfb0309aec67f282200eef05efe0d5bd] [Current]
F   P       [Kendall tau Correlation Matrix] [Kendall's tau Cor...] [2010-12-13 15:59:58] [2843717cd92615903379c14ebee3c5df]
Feedback Forum
2010-12-18 10:12:43 [00c625c7d009d84797af914265b614f9] [reply
Correct,
We zien duidelijk aan de grafiek dat de assumpties voor normaliteit niet voldaan zijn. Aangezien de Pearson Correlation Matrix uitgaat van normaliteit moeten we stellen da we de correlatie beter op een andere manier bekijken.

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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108963&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108963&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108963&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=pearson)
GenderLearningConcernDoubtsCriticismStandardsOrganization
Gender1-0.113-0.0870.172-0.188-0.10.269
Learning-0.1131-0.019-0.3180.0320.2080.248
Concern-0.087-0.01910.3760.2420.4170.069
Doubts0.172-0.3180.37610.088-0.0440.057
Criticism-0.1880.0320.2420.08810.181-0.183
Standards-0.10.2080.417-0.0440.18110.356
Organization0.2690.2480.0690.057-0.1830.3561

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Gender & Learning & Concern & Doubts & Criticism & Standards & Organization \tabularnewline
Gender & 1 & -0.113 & -0.087 & 0.172 & -0.188 & -0.1 & 0.269 \tabularnewline
Learning & -0.113 & 1 & -0.019 & -0.318 & 0.032 & 0.208 & 0.248 \tabularnewline
Concern & -0.087 & -0.019 & 1 & 0.376 & 0.242 & 0.417 & 0.069 \tabularnewline
Doubts & 0.172 & -0.318 & 0.376 & 1 & 0.088 & -0.044 & 0.057 \tabularnewline
Criticism & -0.188 & 0.032 & 0.242 & 0.088 & 1 & 0.181 & -0.183 \tabularnewline
Standards & -0.1 & 0.208 & 0.417 & -0.044 & 0.181 & 1 & 0.356 \tabularnewline
Organization & 0.269 & 0.248 & 0.069 & 0.057 & -0.183 & 0.356 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108963&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/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]-0.113[/C][C]-0.087[/C][C]0.172[/C][C]-0.188[/C][C]-0.1[/C][C]0.269[/C][/ROW]
[ROW][C]Learning[/C][C]-0.113[/C][C]1[/C][C]-0.019[/C][C]-0.318[/C][C]0.032[/C][C]0.208[/C][C]0.248[/C][/ROW]
[ROW][C]Concern[/C][C]-0.087[/C][C]-0.019[/C][C]1[/C][C]0.376[/C][C]0.242[/C][C]0.417[/C][C]0.069[/C][/ROW]
[ROW][C]Doubts[/C][C]0.172[/C][C]-0.318[/C][C]0.376[/C][C]1[/C][C]0.088[/C][C]-0.044[/C][C]0.057[/C][/ROW]
[ROW][C]Criticism[/C][C]-0.188[/C][C]0.032[/C][C]0.242[/C][C]0.088[/C][C]1[/C][C]0.181[/C][C]-0.183[/C][/ROW]
[ROW][C]Standards[/C][C]-0.1[/C][C]0.208[/C][C]0.417[/C][C]-0.044[/C][C]0.181[/C][C]1[/C][C]0.356[/C][/ROW]
[ROW][C]Organization[/C][C]0.269[/C][C]0.248[/C][C]0.069[/C][C]0.057[/C][C]-0.183[/C][C]0.356[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108963&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108963&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)
GenderLearningConcernDoubtsCriticismStandardsOrganization
Gender1-0.113-0.0870.172-0.188-0.10.269
Learning-0.1131-0.019-0.3180.0320.2080.248
Concern-0.087-0.01910.3760.2420.4170.069
Doubts0.172-0.3180.37610.088-0.0440.057
Criticism-0.1880.0320.2420.08810.181-0.183
Standards-0.10.2080.417-0.0440.18110.356
Organization0.2690.2480.0690.057-0.1830.3561







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=108963&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=108963&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108963&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 = 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')