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Description of Statistical Computation

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, 13 Dec 2011 12:46:39 -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/13/t132379843918w8tg89g8o6uud.htm/, Retrieved Fri, 01 Nov 2024 00:30:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154580, Retrieved Fri, 01 Nov 2024 00:30:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99

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-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2	41	38	13	12	14
2	39	32	16	11	18
2	30	35	19	15	11
1	31	33	15	6	12
2	34	37	14	13	16
2	35	29	13	10	18
2	39	31	19	12	14
2	34	36	15	14	14
2	36	35	14	12	15
2	37	38	15	6	15
1	38	31	16	10	17
2	36	34	16	12	19
1	38	35	16	12	10
2	39	38	16	11	16
2	33	37	17	15	18
1	32	33	15	12	14
1	36	32	15	10	14
2	38	38	20	12	17
1	39	38	18	11	14
2	32	32	16	12	16
1	32	33	16	11	18
2	31	31	16	12	11
2	39	38	19	13	14
2	37	39	16	11	12
1	39	32	17	9	17
2	41	32	17	13	9
1	36	35	16	10	16
2	33	37	15	14	14
2	33	33	16	12	15
1	34	33	14	10	11
2	31	28	15	12	16
1	27	32	12	8	13
2	37	31	14	10	17
2	34	37	16	12	15
1	34	30	14	12	14
1	32	33	7	7	16
1	29	31	10	6	9
1	36	33	14	12	15
2	29	31	16	10	17
1	35	33	16	10	13
1	37	32	16	10	15
2	34	33	14	12	16
1	38	32	20	15	16
1	35	33	14	10	12
2	38	28	14	10	12
2	37	35	11	12	11
2	38	39	14	13	15
2	33	34	15	11	15
2	36	38	16	11	17
1	38	32	14	12	13
2	32	38	16	14	16
1	32	30	14	10	14
1	32	33	12	12	11
2	34	38	16	13	12
1	32	32	9	5	12
2	37	32	14	6	15
2	39	34	16	12	16
2	29	34	16	12	15
1	37	36	15	11	12
2	35	34	16	10	12
1	30	28	12	7	8
1	38	34	16	12	13
2	34	35	16	14	11
2	31	35	14	11	14
2	34	31	16	12	15
1	35	37	17	13	10
2	36	35	18	14	11
1	30	27	18	11	12
2	39	40	12	12	15
1	35	37	16	12	15
1	38	36	10	8	14
2	31	38	14	11	16
2	34	39	18	14	15
1	38	41	18	14	15
1	34	27	16	12	13
2	39	30	17	9	12
2	37	37	16	13	17
2	34	31	16	11	13
1	28	31	13	12	15
1	37	27	16	12	13
1	33	36	16	12	15
1	37	38	20	12	16
2	35	37	16	12	15
1	37	33	15	12	16
2	32	34	15	11	15
2	33	31	16	10	14
1	38	39	14	9	15
2	33	34	16	12	14
2	29	32	16	12	13
2	33	33	15	12	7
2	31	36	12	9	17
2	36	32	17	15	13
2	35	41	16	12	15
2	32	28	15	12	14
2	29	30	13	12	13
2	39	36	16	10	16
2	37	35	16	13	12
2	35	31	16	9	14
1	37	34	16	12	17
1	32	36	14	10	15
2	38	36	16	14	17
1	37	35	16	11	12
2	36	37	20	15	16
1	32	28	15	11	11
2	33	39	16	11	15
1	40	32	13	12	9
2	38	35	17	12	16
1	41	39	16	12	15
1	36	35	16	11	10
2	43	42	12	7	10
2	30	34	16	12	15
2	31	33	16	14	11
2	32	41	17	11	13
1	32	33	13	11	14
2	37	34	12	10	18
1	37	32	18	13	16
2	33	40	14	13	14
2	34	40	14	8	14
2	33	35	13	11	14
2	38	36	16	12	14
2	33	37	13	11	12
2	31	27	16	13	14
2	38	39	13	12	15
2	37	38	16	14	15
2	33	31	15	13	15
2	31	33	16	15	13
1	39	32	15	10	17
2	44	39	17	11	17
2	33	36	15	9	19
2	35	33	12	11	15
1	32	33	16	10	13
1	28	32	10	11	9
2	40	37	16	8	15
1	27	30	12	11	15
1	37	38	14	12	15
2	32	29	15	12	16
1	28	22	13	9	11
1	34	35	15	11	14
2	30	35	11	10	11
2	35	34	12	8	15
1	31	35	8	9	13
2	32	34	16	8	15
1	30	34	15	9	16
2	30	35	17	15	14
1	31	23	16	11	15
2	40	31	10	8	16
2	32	27	18	13	16
1	36	36	13	12	11
1	32	31	16	12	12
1	35	32	13	9	9
2	38	39	10	7	16
2	42	37	15	13	13
1	34	38	16	9	16
2	35	39	16	6	12
2	35	34	14	8	9
2	33	31	10	8	13
2	36	32	17	15	13
2	32	37	13	6	14
2	33	36	15	9	19
2	34	32	16	11	13
2	32	35	12	8	12
2	34	36	13	8	13

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154580&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154580&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154580&T=0

As an alternative you can also use a QR Code:  
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'Herman Ole Andreas Wold' @ wold.wessa.net






Correlations for all pairs of data series (method=kendall)
GeslachtConnectedSeparateLearningSoftwareHappiness
Geslacht10.030.1940.0950.1660.142
Connected0.0310.2410.1590.0550.127
Separate0.1940.24110.0670.0790.11
Learning0.0950.1590.06710.3910.12
Software0.1660.0550.0790.39110.024
Happiness0.1420.1270.110.120.0241

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Geslacht & Connected & Separate & Learning & Software & Happiness \tabularnewline
Geslacht & 1 & 0.03 & 0.194 & 0.095 & 0.166 & 0.142 \tabularnewline
Connected & 0.03 & 1 & 0.241 & 0.159 & 0.055 & 0.127 \tabularnewline
Separate & 0.194 & 0.241 & 1 & 0.067 & 0.079 & 0.11 \tabularnewline
Learning & 0.095 & 0.159 & 0.067 & 1 & 0.391 & 0.12 \tabularnewline
Software & 0.166 & 0.055 & 0.079 & 0.391 & 1 & 0.024 \tabularnewline
Happiness & 0.142 & 0.127 & 0.11 & 0.12 & 0.024 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154580&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Geslacht[/C][C]Connected[/C][C]Separate[/C][C]Learning[/C][C]Software[/C][C]Happiness[/C][/ROW]
[ROW][C]Geslacht[/C][C]1[/C][C]0.03[/C][C]0.194[/C][C]0.095[/C][C]0.166[/C][C]0.142[/C][/ROW]
[ROW][C]Connected[/C][C]0.03[/C][C]1[/C][C]0.241[/C][C]0.159[/C][C]0.055[/C][C]0.127[/C][/ROW]
[ROW][C]Separate[/C][C]0.194[/C][C]0.241[/C][C]1[/C][C]0.067[/C][C]0.079[/C][C]0.11[/C][/ROW]
[ROW][C]Learning[/C][C]0.095[/C][C]0.159[/C][C]0.067[/C][C]1[/C][C]0.391[/C][C]0.12[/C][/ROW]
[ROW][C]Software[/C][C]0.166[/C][C]0.055[/C][C]0.079[/C][C]0.391[/C][C]1[/C][C]0.024[/C][/ROW]
[ROW][C]Happiness[/C][C]0.142[/C][C]0.127[/C][C]0.11[/C][C]0.12[/C][C]0.024[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154580&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154580&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=kendall)
GeslachtConnectedSeparateLearningSoftwareHappiness
Geslacht10.030.1940.0950.1660.142
Connected0.0310.2410.1590.0550.127
Separate0.1940.24110.0670.0790.11
Learning0.0950.1590.06710.3910.12
Software0.1660.0550.0790.39110.024
Happiness0.1420.1270.110.120.0241






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Geslacht;Connected0.06450.03570.0304
p-value(0.4149)(0.652)(0.6505)
Geslacht;Separate0.23980.22830.1941
p-value(0.0021)(0.0035)(0.0038)
Geslacht;Learning0.11890.10770.0948
p-value(0.1319)(0.1724)(0.1717)
Geslacht;Software0.16340.18980.166
p-value(0.0377)(0.0156)(0.016)
Geslacht;Happiness0.18180.16430.1422
p-value(0.0206)(0.0367)(0.0371)
Connected;Separate0.36820.32430.2413
p-value(0)(0)(0)
Connected;Learning0.21370.20760.1586
p-value(0.0063)(0.008)(0.0072)
Connected;Software0.06220.07480.0549
p-value(0.4317)(0.3439)(0.3491)
Connected;Happiness0.14270.17170.1274
p-value(0.0701)(0.0289)(0.0283)
Separate;Learning0.07960.08780.0665
p-value(0.3139)(0.2666)(0.2597)
Separate;Software0.06790.11110.0787
p-value(0.3906)(0.1594)(0.1795)
Separate;Happiness0.15370.15430.1097
p-value(0.0509)(0.05)(0.0589)
Learning;Software0.54560.48810.3906
p-value(0)(0)(0)
Learning;Happiness0.18290.15530.1199
p-value(0.0198)(0.0484)(0.0461)
Software;Happiness0.0740.03120.0241
p-value(0.3492)(0.6933)(0.6863)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Geslacht;Connected & 0.0645 & 0.0357 & 0.0304 \tabularnewline
p-value & (0.4149) & (0.652) & (0.6505) \tabularnewline
Geslacht;Separate & 0.2398 & 0.2283 & 0.1941 \tabularnewline
p-value & (0.0021) & (0.0035) & (0.0038) \tabularnewline
Geslacht;Learning & 0.1189 & 0.1077 & 0.0948 \tabularnewline
p-value & (0.1319) & (0.1724) & (0.1717) \tabularnewline
Geslacht;Software & 0.1634 & 0.1898 & 0.166 \tabularnewline
p-value & (0.0377) & (0.0156) & (0.016) \tabularnewline
Geslacht;Happiness & 0.1818 & 0.1643 & 0.1422 \tabularnewline
p-value & (0.0206) & (0.0367) & (0.0371) \tabularnewline
Connected;Separate & 0.3682 & 0.3243 & 0.2413 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Connected;Learning & 0.2137 & 0.2076 & 0.1586 \tabularnewline
p-value & (0.0063) & (0.008) & (0.0072) \tabularnewline
Connected;Software & 0.0622 & 0.0748 & 0.0549 \tabularnewline
p-value & (0.4317) & (0.3439) & (0.3491) \tabularnewline
Connected;Happiness & 0.1427 & 0.1717 & 0.1274 \tabularnewline
p-value & (0.0701) & (0.0289) & (0.0283) \tabularnewline
Separate;Learning & 0.0796 & 0.0878 & 0.0665 \tabularnewline
p-value & (0.3139) & (0.2666) & (0.2597) \tabularnewline
Separate;Software & 0.0679 & 0.1111 & 0.0787 \tabularnewline
p-value & (0.3906) & (0.1594) & (0.1795) \tabularnewline
Separate;Happiness & 0.1537 & 0.1543 & 0.1097 \tabularnewline
p-value & (0.0509) & (0.05) & (0.0589) \tabularnewline
Learning;Software & 0.5456 & 0.4881 & 0.3906 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Learning;Happiness & 0.1829 & 0.1553 & 0.1199 \tabularnewline
p-value & (0.0198) & (0.0484) & (0.0461) \tabularnewline
Software;Happiness & 0.074 & 0.0312 & 0.0241 \tabularnewline
p-value & (0.3492) & (0.6933) & (0.6863) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154580&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]Geslacht;Connected[/C][C]0.0645[/C][C]0.0357[/C][C]0.0304[/C][/ROW]
[ROW][C]p-value[/C][C](0.4149)[/C][C](0.652)[/C][C](0.6505)[/C][/ROW]
[ROW][C]Geslacht;Separate[/C][C]0.2398[/C][C]0.2283[/C][C]0.1941[/C][/ROW]
[ROW][C]p-value[/C][C](0.0021)[/C][C](0.0035)[/C][C](0.0038)[/C][/ROW]
[ROW][C]Geslacht;Learning[/C][C]0.1189[/C][C]0.1077[/C][C]0.0948[/C][/ROW]
[ROW][C]p-value[/C][C](0.1319)[/C][C](0.1724)[/C][C](0.1717)[/C][/ROW]
[ROW][C]Geslacht;Software[/C][C]0.1634[/C][C]0.1898[/C][C]0.166[/C][/ROW]
[ROW][C]p-value[/C][C](0.0377)[/C][C](0.0156)[/C][C](0.016)[/C][/ROW]
[ROW][C]Geslacht;Happiness[/C][C]0.1818[/C][C]0.1643[/C][C]0.1422[/C][/ROW]
[ROW][C]p-value[/C][C](0.0206)[/C][C](0.0367)[/C][C](0.0371)[/C][/ROW]
[ROW][C]Connected;Separate[/C][C]0.3682[/C][C]0.3243[/C][C]0.2413[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Connected;Learning[/C][C]0.2137[/C][C]0.2076[/C][C]0.1586[/C][/ROW]
[ROW][C]p-value[/C][C](0.0063)[/C][C](0.008)[/C][C](0.0072)[/C][/ROW]
[ROW][C]Connected;Software[/C][C]0.0622[/C][C]0.0748[/C][C]0.0549[/C][/ROW]
[ROW][C]p-value[/C][C](0.4317)[/C][C](0.3439)[/C][C](0.3491)[/C][/ROW]
[ROW][C]Connected;Happiness[/C][C]0.1427[/C][C]0.1717[/C][C]0.1274[/C][/ROW]
[ROW][C]p-value[/C][C](0.0701)[/C][C](0.0289)[/C][C](0.0283)[/C][/ROW]
[ROW][C]Separate;Learning[/C][C]0.0796[/C][C]0.0878[/C][C]0.0665[/C][/ROW]
[ROW][C]p-value[/C][C](0.3139)[/C][C](0.2666)[/C][C](0.2597)[/C][/ROW]
[ROW][C]Separate;Software[/C][C]0.0679[/C][C]0.1111[/C][C]0.0787[/C][/ROW]
[ROW][C]p-value[/C][C](0.3906)[/C][C](0.1594)[/C][C](0.1795)[/C][/ROW]
[ROW][C]Separate;Happiness[/C][C]0.1537[/C][C]0.1543[/C][C]0.1097[/C][/ROW]
[ROW][C]p-value[/C][C](0.0509)[/C][C](0.05)[/C][C](0.0589)[/C][/ROW]
[ROW][C]Learning;Software[/C][C]0.5456[/C][C]0.4881[/C][C]0.3906[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Learning;Happiness[/C][C]0.1829[/C][C]0.1553[/C][C]0.1199[/C][/ROW]
[ROW][C]p-value[/C][C](0.0198)[/C][C](0.0484)[/C][C](0.0461)[/C][/ROW]
[ROW][C]Software;Happiness[/C][C]0.074[/C][C]0.0312[/C][C]0.0241[/C][/ROW]
[ROW][C]p-value[/C][C](0.3492)[/C][C](0.6933)[/C][C](0.6863)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154580&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154580&T=2

As an alternative you can also use a QR Code:  
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
Geslacht;Connected0.06450.03570.0304
p-value(0.4149)(0.652)(0.6505)
Geslacht;Separate0.23980.22830.1941
p-value(0.0021)(0.0035)(0.0038)
Geslacht;Learning0.11890.10770.0948
p-value(0.1319)(0.1724)(0.1717)
Geslacht;Software0.16340.18980.166
p-value(0.0377)(0.0156)(0.016)
Geslacht;Happiness0.18180.16430.1422
p-value(0.0206)(0.0367)(0.0371)
Connected;Separate0.36820.32430.2413
p-value(0)(0)(0)
Connected;Learning0.21370.20760.1586
p-value(0.0063)(0.008)(0.0072)
Connected;Software0.06220.07480.0549
p-value(0.4317)(0.3439)(0.3491)
Connected;Happiness0.14270.17170.1274
p-value(0.0701)(0.0289)(0.0283)
Separate;Learning0.07960.08780.0665
p-value(0.3139)(0.2666)(0.2597)
Separate;Software0.06790.11110.0787
p-value(0.3906)(0.1594)(0.1795)
Separate;Happiness0.15370.15430.1097
p-value(0.0509)(0.05)(0.0589)
Learning;Software0.54560.48810.3906
p-value(0)(0)(0)
Learning;Happiness0.18290.15530.1199
p-value(0.0198)(0.0484)(0.0461)
Software;Happiness0.0740.03120.0241
p-value(0.3492)(0.6933)(0.6863)


Figures (Output of Computation)

Input Parameters & R Code

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')