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R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSat, 08 Dec 2012 10:44:14 -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/08/t1354981515s77i000ojojnhdn.htm/, Retrieved Tue, 16 Apr 2024 17:26:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197659, Retrieved Tue, 16 Apr 2024 17:26:54 +0000
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Estimated Impact90
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-       [Kendall tau Correlation Matrix] [ws10: kendall tau] [2012-12-08 15:44:14] [5948b95c00a54abd73f88aac58cf0e09] [Current]
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Dataseries X:
 25      2      10      1.5        0        6    5.70     11.40
 24      2      10      1.5        0       10   17.56     35.12
 30      2      10      1.5        2        6   11.28     22.56
  2      2      10      1.5        2       10    8.39     16.78
 40      2      10      2.5        0        6   16.67     33.34
 37      2      10      2.5        0       10   12.04     24.08
 16      2      10      2.5        2        6    9.22     18.44
 22      2      10      2.5        2       10    3.94      7.88
 33      2      30      1.5        0        6   27.02     18.01
 17      2      30      1.5        0       10   19.46     12.97
 28      2      30      1.5        2        6   18.54     12.36
 27      2      30      1.5        2       10   25.70     17.13
 14      2      30      2.5        0        6   19.02     12.68
 13      2      30      2.5        0       10   22.39     14.93
  4      2      30      2.5        2        6   23.85     15.90
 21      2      30      2.5        2       10   30.12     20.08
 23      6      10      1.5        0        6   13.42     26.84
 35      6      10      1.5        0       10   34.26     68.52
 19      6      10      1.5        2        6   39.74     79.48
 34      6      10      1.5        2       10   10.60     21.20
 31      6      10      2.5        0        6   28.89     57.78
  9      6      10      2.5        0       10   35.61     71.22
 38      6      10      2.5        2        6   17.20     34.40
 15      6      10      2.5        2       10    6.00     12.00
 39      6      30      1.5        0        6  129.45     86.30
  8      6      30      1.5        0       10  107.38     71.59
 26      6      30      1.5        2        6  111.66     74.44
 11      6      30      1.5        2       10  109.10     72.73
  6      6      30      2.5        0        6  100.43     66.95
 20      6      30      2.5        0       10  109.28     72.85
 10      6      30      2.5        2        6  106.46     70.97
 32      6      30      2.5        2       10  134.01     89.34
  1      4      20      2.0        1        8   10.78     10.78
  3      4      20      2.0        1        8    9.39      9.39
  5      4      20      2.0        1        8    9.84      9.84
  7      4      20      2.0        1        8   13.94     13.94
 12      4      20      2.0        1        8   12.33     12.33
 18      4      20      2.0        1        8    7.32      7.32
 29      4      20      2.0        1        8    7.91      7.91
 36      4      20      2.0        1        8   15.58     15.58




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197659&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197659&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197659&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' @ jenkins.wessa.net







Correlations for all pairs of data series (method=pearson)
RUNSPEED1TOTALSPEED2NUMBER2SENSTIMET20BOLT
RUN10.007-0.22-0.128-0.094-0.1330.0120.137
SPEED10.007100000.5780.705
TOTAL-0.22010000.5780.194
SPEED2-0.12800100-0.01-0.025
NUMBER2-0.09400010-0.023-0.102
SENS-0.133000010.005-0.014
TIME0.0120.5780.578-0.01-0.0230.00510.862
T20BOLT0.1370.7050.194-0.025-0.102-0.0140.8621

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & RUN & SPEED1 & TOTAL & SPEED2 & NUMBER2 & SENS & TIME & T20BOLT \tabularnewline
RUN & 1 & 0.007 & -0.22 & -0.128 & -0.094 & -0.133 & 0.012 & 0.137 \tabularnewline
SPEED1 & 0.007 & 1 & 0 & 0 & 0 & 0 & 0.578 & 0.705 \tabularnewline
TOTAL & -0.22 & 0 & 1 & 0 & 0 & 0 & 0.578 & 0.194 \tabularnewline
SPEED2 & -0.128 & 0 & 0 & 1 & 0 & 0 & -0.01 & -0.025 \tabularnewline
NUMBER2 & -0.094 & 0 & 0 & 0 & 1 & 0 & -0.023 & -0.102 \tabularnewline
SENS & -0.133 & 0 & 0 & 0 & 0 & 1 & 0.005 & -0.014 \tabularnewline
TIME & 0.012 & 0.578 & 0.578 & -0.01 & -0.023 & 0.005 & 1 & 0.862 \tabularnewline
T20BOLT & 0.137 & 0.705 & 0.194 & -0.025 & -0.102 & -0.014 & 0.862 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197659&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]RUN[/C][C]SPEED1[/C][C]TOTAL[/C][C]SPEED2[/C][C]NUMBER2[/C][C]SENS[/C][C]TIME[/C][C]T20BOLT[/C][/ROW]
[ROW][C]RUN[/C][C]1[/C][C]0.007[/C][C]-0.22[/C][C]-0.128[/C][C]-0.094[/C][C]-0.133[/C][C]0.012[/C][C]0.137[/C][/ROW]
[ROW][C]SPEED1[/C][C]0.007[/C][C]1[/C][C]0[/C][C]0[/C][C]0[/C][C]0[/C][C]0.578[/C][C]0.705[/C][/ROW]
[ROW][C]TOTAL[/C][C]-0.22[/C][C]0[/C][C]1[/C][C]0[/C][C]0[/C][C]0[/C][C]0.578[/C][C]0.194[/C][/ROW]
[ROW][C]SPEED2[/C][C]-0.128[/C][C]0[/C][C]0[/C][C]1[/C][C]0[/C][C]0[/C][C]-0.01[/C][C]-0.025[/C][/ROW]
[ROW][C]NUMBER2[/C][C]-0.094[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0[/C][C]-0.023[/C][C]-0.102[/C][/ROW]
[ROW][C]SENS[/C][C]-0.133[/C][C]0[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0.005[/C][C]-0.014[/C][/ROW]
[ROW][C]TIME[/C][C]0.012[/C][C]0.578[/C][C]0.578[/C][C]-0.01[/C][C]-0.023[/C][C]0.005[/C][C]1[/C][C]0.862[/C][/ROW]
[ROW][C]T20BOLT[/C][C]0.137[/C][C]0.705[/C][C]0.194[/C][C]-0.025[/C][C]-0.102[/C][C]-0.014[/C][C]0.862[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197659&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197659&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)
RUNSPEED1TOTALSPEED2NUMBER2SENSTIMET20BOLT
RUN10.007-0.22-0.128-0.094-0.1330.0120.137
SPEED10.007100000.5780.705
TOTAL-0.22010000.5780.194
SPEED2-0.12800100-0.01-0.025
NUMBER2-0.09400010-0.023-0.102
SENS-0.133000010.005-0.014
TIME0.0120.5780.578-0.01-0.0230.00510.862
T20BOLT0.1370.7050.194-0.025-0.102-0.0140.8621







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
RUN;SPEED10.00730.00730.0095
p-value(0.9645)(0.9645)(0.9398)
RUN;TOTAL-0.2203-0.2203-0.1646
p-value(0.1719)(0.1719)(0.1906)
RUN;SPEED2-0.1283-0.1283-0.0886
p-value(0.43)(0.43)(0.481)
RUN;NUMBER2-0.0944-0.0944-0.076
p-value(0.5622)(0.5622)(0.5458)
RUN;SENS-0.1332-0.1332-0.0981
p-value(0.4127)(0.4127)(0.4353)
RUN;TIME0.01210.0970.0641
p-value(0.9411)(0.5503)(0.5704)
RUN;T20BOLT0.13670.27950.1974
p-value(0.4003)(0.0809)(0.0745)
SPEED1;TOTAL000
p-value(1)(1)(1)
SPEED1;SPEED2000
p-value(1)(1)(1)
SPEED1;NUMBER2000
p-value(1)(1)(1)
SPEED1;SENS000
p-value(1)(1)(1)
SPEED1;TIME0.57790.44550.3228
p-value(1e-04)(0.004)(0.0103)
SPEED1;T20BOLT0.70530.55210.3829
p-value(0)(2e-04)(0.0023)
TOTAL;SPEED2000
p-value(1)(1)(1)
TOTAL;NUMBER2000
p-value(1)(1)(1)
TOTAL;SENS000
p-value(1)(1)(1)
TOTAL;TIME0.57850.5860.4589
p-value(1e-04)(1e-04)(3e-04)
TOTAL;T20BOLT0.19430.10650.0791
p-value(0.2295)(0.5129)(0.5292)
SPEED2;NUMBER2000
p-value(1)(1)(1)
SPEED2;SENS000
p-value(1)(1)(1)
SPEED2;TIME-0.0099-0.0194-0.0158
p-value(0.9515)(0.9056)(0.8999)
SPEED2;T20BOLT-0.0254-0.063-0.0506
p-value(0.8764)(0.6996)(0.6872)
NUMBER2;SENS000
p-value(1)(1)(1)
NUMBER2;TIME-0.023-0.1404-0.1266
p-value(0.8879)(0.3874)(0.3141)
NUMBER2;T20BOLT-0.1021-0.0775-0.057
p-value(0.5306)(0.6346)(0.6505)
SENS;TIME0.0051-0.0194-0.0285
p-value(0.975)(0.9056)(0.8208)
SENS;T20BOLT-0.0139-0.0339-0.0316
p-value(0.9323)(0.8355)(0.8013)
TIME;T20BOLT0.86190.81970.6923
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
RUN;SPEED1 & 0.0073 & 0.0073 & 0.0095 \tabularnewline
p-value & (0.9645) & (0.9645) & (0.9398) \tabularnewline
RUN;TOTAL & -0.2203 & -0.2203 & -0.1646 \tabularnewline
p-value & (0.1719) & (0.1719) & (0.1906) \tabularnewline
RUN;SPEED2 & -0.1283 & -0.1283 & -0.0886 \tabularnewline
p-value & (0.43) & (0.43) & (0.481) \tabularnewline
RUN;NUMBER2 & -0.0944 & -0.0944 & -0.076 \tabularnewline
p-value & (0.5622) & (0.5622) & (0.5458) \tabularnewline
RUN;SENS & -0.1332 & -0.1332 & -0.0981 \tabularnewline
p-value & (0.4127) & (0.4127) & (0.4353) \tabularnewline
RUN;TIME & 0.0121 & 0.097 & 0.0641 \tabularnewline
p-value & (0.9411) & (0.5503) & (0.5704) \tabularnewline
RUN;T20BOLT & 0.1367 & 0.2795 & 0.1974 \tabularnewline
p-value & (0.4003) & (0.0809) & (0.0745) \tabularnewline
SPEED1;TOTAL & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
SPEED1;SPEED2 & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
SPEED1;NUMBER2 & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
SPEED1;SENS & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
SPEED1;TIME & 0.5779 & 0.4455 & 0.3228 \tabularnewline
p-value & (1e-04) & (0.004) & (0.0103) \tabularnewline
SPEED1;T20BOLT & 0.7053 & 0.5521 & 0.3829 \tabularnewline
p-value & (0) & (2e-04) & (0.0023) \tabularnewline
TOTAL;SPEED2 & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
TOTAL;NUMBER2 & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
TOTAL;SENS & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
TOTAL;TIME & 0.5785 & 0.586 & 0.4589 \tabularnewline
p-value & (1e-04) & (1e-04) & (3e-04) \tabularnewline
TOTAL;T20BOLT & 0.1943 & 0.1065 & 0.0791 \tabularnewline
p-value & (0.2295) & (0.5129) & (0.5292) \tabularnewline
SPEED2;NUMBER2 & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
SPEED2;SENS & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
SPEED2;TIME & -0.0099 & -0.0194 & -0.0158 \tabularnewline
p-value & (0.9515) & (0.9056) & (0.8999) \tabularnewline
SPEED2;T20BOLT & -0.0254 & -0.063 & -0.0506 \tabularnewline
p-value & (0.8764) & (0.6996) & (0.6872) \tabularnewline
NUMBER2;SENS & 0 & 0 & 0 \tabularnewline
p-value & (1) & (1) & (1) \tabularnewline
NUMBER2;TIME & -0.023 & -0.1404 & -0.1266 \tabularnewline
p-value & (0.8879) & (0.3874) & (0.3141) \tabularnewline
NUMBER2;T20BOLT & -0.1021 & -0.0775 & -0.057 \tabularnewline
p-value & (0.5306) & (0.6346) & (0.6505) \tabularnewline
SENS;TIME & 0.0051 & -0.0194 & -0.0285 \tabularnewline
p-value & (0.975) & (0.9056) & (0.8208) \tabularnewline
SENS;T20BOLT & -0.0139 & -0.0339 & -0.0316 \tabularnewline
p-value & (0.9323) & (0.8355) & (0.8013) \tabularnewline
TIME;T20BOLT & 0.8619 & 0.8197 & 0.6923 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197659&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]RUN;SPEED1[/C][C]0.0073[/C][C]0.0073[/C][C]0.0095[/C][/ROW]
[ROW][C]p-value[/C][C](0.9645)[/C][C](0.9645)[/C][C](0.9398)[/C][/ROW]
[ROW][C]RUN;TOTAL[/C][C]-0.2203[/C][C]-0.2203[/C][C]-0.1646[/C][/ROW]
[ROW][C]p-value[/C][C](0.1719)[/C][C](0.1719)[/C][C](0.1906)[/C][/ROW]
[ROW][C]RUN;SPEED2[/C][C]-0.1283[/C][C]-0.1283[/C][C]-0.0886[/C][/ROW]
[ROW][C]p-value[/C][C](0.43)[/C][C](0.43)[/C][C](0.481)[/C][/ROW]
[ROW][C]RUN;NUMBER2[/C][C]-0.0944[/C][C]-0.0944[/C][C]-0.076[/C][/ROW]
[ROW][C]p-value[/C][C](0.5622)[/C][C](0.5622)[/C][C](0.5458)[/C][/ROW]
[ROW][C]RUN;SENS[/C][C]-0.1332[/C][C]-0.1332[/C][C]-0.0981[/C][/ROW]
[ROW][C]p-value[/C][C](0.4127)[/C][C](0.4127)[/C][C](0.4353)[/C][/ROW]
[ROW][C]RUN;TIME[/C][C]0.0121[/C][C]0.097[/C][C]0.0641[/C][/ROW]
[ROW][C]p-value[/C][C](0.9411)[/C][C](0.5503)[/C][C](0.5704)[/C][/ROW]
[ROW][C]RUN;T20BOLT[/C][C]0.1367[/C][C]0.2795[/C][C]0.1974[/C][/ROW]
[ROW][C]p-value[/C][C](0.4003)[/C][C](0.0809)[/C][C](0.0745)[/C][/ROW]
[ROW][C]SPEED1;TOTAL[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]SPEED1;SPEED2[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]SPEED1;NUMBER2[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]SPEED1;SENS[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]SPEED1;TIME[/C][C]0.5779[/C][C]0.4455[/C][C]0.3228[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0.004)[/C][C](0.0103)[/C][/ROW]
[ROW][C]SPEED1;T20BOLT[/C][C]0.7053[/C][C]0.5521[/C][C]0.3829[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](2e-04)[/C][C](0.0023)[/C][/ROW]
[ROW][C]TOTAL;SPEED2[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]TOTAL;NUMBER2[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]TOTAL;SENS[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]TOTAL;TIME[/C][C]0.5785[/C][C]0.586[/C][C]0.4589[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](1e-04)[/C][C](3e-04)[/C][/ROW]
[ROW][C]TOTAL;T20BOLT[/C][C]0.1943[/C][C]0.1065[/C][C]0.0791[/C][/ROW]
[ROW][C]p-value[/C][C](0.2295)[/C][C](0.5129)[/C][C](0.5292)[/C][/ROW]
[ROW][C]SPEED2;NUMBER2[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]SPEED2;SENS[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]SPEED2;TIME[/C][C]-0.0099[/C][C]-0.0194[/C][C]-0.0158[/C][/ROW]
[ROW][C]p-value[/C][C](0.9515)[/C][C](0.9056)[/C][C](0.8999)[/C][/ROW]
[ROW][C]SPEED2;T20BOLT[/C][C]-0.0254[/C][C]-0.063[/C][C]-0.0506[/C][/ROW]
[ROW][C]p-value[/C][C](0.8764)[/C][C](0.6996)[/C][C](0.6872)[/C][/ROW]
[ROW][C]NUMBER2;SENS[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](1)[/C][C](1)[/C][/ROW]
[ROW][C]NUMBER2;TIME[/C][C]-0.023[/C][C]-0.1404[/C][C]-0.1266[/C][/ROW]
[ROW][C]p-value[/C][C](0.8879)[/C][C](0.3874)[/C][C](0.3141)[/C][/ROW]
[ROW][C]NUMBER2;T20BOLT[/C][C]-0.1021[/C][C]-0.0775[/C][C]-0.057[/C][/ROW]
[ROW][C]p-value[/C][C](0.5306)[/C][C](0.6346)[/C][C](0.6505)[/C][/ROW]
[ROW][C]SENS;TIME[/C][C]0.0051[/C][C]-0.0194[/C][C]-0.0285[/C][/ROW]
[ROW][C]p-value[/C][C](0.975)[/C][C](0.9056)[/C][C](0.8208)[/C][/ROW]
[ROW][C]SENS;T20BOLT[/C][C]-0.0139[/C][C]-0.0339[/C][C]-0.0316[/C][/ROW]
[ROW][C]p-value[/C][C](0.9323)[/C][C](0.8355)[/C][C](0.8013)[/C][/ROW]
[ROW][C]TIME;T20BOLT[/C][C]0.8619[/C][C]0.8197[/C][C]0.6923[/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=197659&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197659&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
RUN;SPEED10.00730.00730.0095
p-value(0.9645)(0.9645)(0.9398)
RUN;TOTAL-0.2203-0.2203-0.1646
p-value(0.1719)(0.1719)(0.1906)
RUN;SPEED2-0.1283-0.1283-0.0886
p-value(0.43)(0.43)(0.481)
RUN;NUMBER2-0.0944-0.0944-0.076
p-value(0.5622)(0.5622)(0.5458)
RUN;SENS-0.1332-0.1332-0.0981
p-value(0.4127)(0.4127)(0.4353)
RUN;TIME0.01210.0970.0641
p-value(0.9411)(0.5503)(0.5704)
RUN;T20BOLT0.13670.27950.1974
p-value(0.4003)(0.0809)(0.0745)
SPEED1;TOTAL000
p-value(1)(1)(1)
SPEED1;SPEED2000
p-value(1)(1)(1)
SPEED1;NUMBER2000
p-value(1)(1)(1)
SPEED1;SENS000
p-value(1)(1)(1)
SPEED1;TIME0.57790.44550.3228
p-value(1e-04)(0.004)(0.0103)
SPEED1;T20BOLT0.70530.55210.3829
p-value(0)(2e-04)(0.0023)
TOTAL;SPEED2000
p-value(1)(1)(1)
TOTAL;NUMBER2000
p-value(1)(1)(1)
TOTAL;SENS000
p-value(1)(1)(1)
TOTAL;TIME0.57850.5860.4589
p-value(1e-04)(1e-04)(3e-04)
TOTAL;T20BOLT0.19430.10650.0791
p-value(0.2295)(0.5129)(0.5292)
SPEED2;NUMBER2000
p-value(1)(1)(1)
SPEED2;SENS000
p-value(1)(1)(1)
SPEED2;TIME-0.0099-0.0194-0.0158
p-value(0.9515)(0.9056)(0.8999)
SPEED2;T20BOLT-0.0254-0.063-0.0506
p-value(0.8764)(0.6996)(0.6872)
NUMBER2;SENS000
p-value(1)(1)(1)
NUMBER2;TIME-0.023-0.1404-0.1266
p-value(0.8879)(0.3874)(0.3141)
NUMBER2;T20BOLT-0.1021-0.0775-0.057
p-value(0.5306)(0.6346)(0.6505)
SENS;TIME0.0051-0.0194-0.0285
p-value(0.975)(0.9056)(0.8208)
SENS;T20BOLT-0.0139-0.0339-0.0316
p-value(0.9323)(0.8355)(0.8013)
TIME;T20BOLT0.86190.81970.6923
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')