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Description of Statistical Computation

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, 20 Dec 2010 11:21:04 +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/20/t1292843964eun2st7y5i000gm.htm/, Retrieved Sat, 04 May 2024 04:14:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112846, Retrieved Sat, 04 May 2024 04:14:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

Tree of Dependent Computations

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]
- R PD  [Kendall tau Correlation Matrix] [] [2010-12-20 10:55:57] [4f1a20f787b3465111b61213cdeef1a9]
-           [Kendall tau Correlation Matrix] [Pearson correlati...] [2010-12-20 11:21:04] [f0b33ae54e73edcd25a3e2f31270d1c9] [Current]
-   P         [Kendall tau Correlation Matrix] [Kendall's tau Cor...] [2010-12-20 13:09:43] [4f1a20f787b3465111b61213cdeef1a9]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
22.037	17.759	14.116	104.708	158.620
21.732	17.530	13.504	101.817	154.583
21.172	17.139	13.168	97.898	149.377
21.388	16.916	13.064	95.559	146.927
22.053	16.543	12.828	92.822	144.246
22.687	16.317	12.541	90.848	142.393
24.793	18.161	13.547	101.141	157.642
26.113	19.144	13.710	105.841	164.808
23.708	16.947	12.535	93.647	146.837
23.554	16.491	12.386	90.923	143.354
23.222	16.428	12.253	89.130	141.033
23.363	16.639	12.484	90.212	142.698
24.023	16.821	12.966	93.196	147.006
23.355	16.765	12.770	91.861	144.751
23.276	16.533	12.660	90.593	143.062
23.085	16.554	12.514	89.895	142.048
23.173	16.494	12.430	88.819	140.916
23.487	16.612	12.372	87.924	140.395
25.576	17.933	13.085	96.906	153.500
26.311	19.070	13.454	101.217	160.052
27.109	18.179	13.361	98.709	157.358
27.060	17.830	13.713	98.139	156.742
26.490	17.349	13.601	95.529	152.969
27.157	17.919	14.090	98.577	157.743
26.973	18.269	14.452	100.772	160.466
27.589	18.385	14.108	100.180	160.262
27.246	18.260	14.036	99.200	158.742
26.845	17.905	13.332	96.251	154.333
26.582	17.730	13.421	94.514	152.247
26.544	17.827	13.279	93.780	151.430
29.105	19.978	14.583	105.192	168.858
28.703	20.315	14.991	107.682	171.691
27.921	18.931	14.313	99.687	160.852
28.566	18.732	14.769	99.436	161.503
29.860	19.155	15.365	102.049	166.429
30.194	19.270	15.448	102.673	167.585
31.330	19.754	16.485	105.813	173.382
31.018	19.845	16.493	105.056	172.412
30.954	19.937	16.748	103.916	171.555
31.398	20.097	16.921	103.513	171.929
31.267	19.981	16.906	101.893	170.047
32.069	20.502	17.050	102.503	172.124
34.665	22.712	18.873	113.149	189.399
35.834	23.101	19.684	116.696	195.315
34.034	21.381	18.260	108.500	182.175
34.435	21.255	18.338	107.800	181.828
34.000	21.053	18.358	105.941	179.352
35.216	21.561	19.394	108.742	184.913
35.734	21.923	20.568	111.680	189.905
35.347	22.001	20.956	111.270	189.574
35.357	22.369	21.523	110.698	189.947
34.802	22.320	22.712	108.517	188.351
34.493	22.149	22.382	107.127	186.151
35.047	22.581	23.168	107.088	187.884
37.386	24.896	24.777	116.321	203.380
38.691	26.610	33.608	125.045	223.954
37.249	25.417	33.137	116.779	212.582
37.668	26.484	34.897	122.887	221.936
36.764	26.329	35.344	120.162	218.599
37.926	26.989	36.152	123.198	224.265
38.145	27.180	37.291	123.610	226.226
37.664	27.284	37.625	122.293	224.866
37.449	27.436	38.034	121.289	224.208
37.389	27.082	38.244	119.393	222.108
37.121	26.818	38.461	117.494	219.894
37.447	27.003	39.078	116.693	220.221
39.751	29.344	40.701	125.062	234.858
40.154	29.777	41.686	127.281	238.898
38.814	28.070	41.294	120.195	228.373
38.673	27.993	41.927	119.804	228.397
37.948	27.672	42.339	117.113	225.072
39.161	27.802	43.170	119.240	229.373
37.408	27.328	43.703	115.823	224.262
37.356	27.666	44.177	116.281	225.480
36.606	27.456	44.703	113.816	222.581
37.040	27.796	45.319	114.632	224.787
36.349	27.642	45.790	112.987	222.768
36.158	27.651	45.838	111.633	221.280
37.342	29.604	46.806	116.721	230.473
36.800	29.196	47.014	114.850	227.860
37.135	28.328	47.381	112.797	225.641
34.265	27.986	47.049	105.368	214.668
33.226	27.738	46.910	102.524	210.398
32.357	27.867	46.853	101.327	208.404
36.870	27.580	46.608	98.873	209.931
35.880	27.381	46.139	95.993	205.393
34.808	27.292	45.954	93.244	201.298
34.025	26.944	45.367	90.403	196.739
33.901	26.329	44.538	88.539	193.307
37.459	29.023	45.897	98.106	210.485
37.152	28.705	45.744	96.963	208.564
34.929	27.213	44.819	90.781	197.742
34.116	27.063	44.836	89.253	195.268
33.710	27.010	44.779	87.794	193.293
34.264	27.709	45.383	89.810	197.166
34.826	27.802	45.613	90.864	199.105
34.096	27.687	45.331	89.025	196.139
33.955	27.719	45.212	87.621	194.507
34.111	27.961	45.329	87.718	195.119
32.344	27.203	44.603	83.433	187.583
32.871	27.747	44.405	84.535	189.558
36.244	30.713	45.701	92.223	204.881
35.988	30.395	45.647	91.052	203.082
35.439	28.895	45.186	88.456	197.976
35.692	28.460	45.113	88.706	197.971
35.804	28.286	45.301	89.137	198.528
37.747	28.984	46.342	94.066	207.139
40.673	29.624	47.309	99.258	216.864
41.601	29.734	47.659	100.673	219.667
42.273	30.603	48.106	102.269	223.251
41.952	30.427	48.087	100.833	221.299
41.463	30.269	48.188	99.314	219.234
42.759	30.798	48.917	101.764	224.238
45.434	32.676	50.312	108.242	236.664
45.776	32.680	50.531	108.148	237.135
44.630	30.737	50.005	104.761	230.133
44.793	30.300	50.306	103.772	229.171
44.757	30.321	50.598	103.737	229.413
49.099	31.282	51.856	111.043	243.280
47.974	30.868	52.132	109.906	240.880
47.919	30.749	52.167	109.335	240.170
47.519	30.236	52.149	107.247	237.151
47.136	29.990	51.976	105.690	234.792
45.910	29.427	51.797	102.755	229.889
46.436	29.376	51.907	102.280	229.999
50.334	30.828	53.589	110.590	245.341
50.294	30.532	53.814	109.122	243.762
47.224	29.166	52.436	102.795	231.621
47.030	29.124	52.448	101.416	230.018
45.790	28.904	52.322	99.138	226.154
38.252	27.992	47.040	102.612	215.896

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112846&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112846&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112846&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Correlations for all pairs of data series (method=pearson)
AllochtonenPmAH50+Kort-geschooldenTotaal_NWW
Allochtonen10.8950.8450.4380.937
PmAH0.89510.9730.2950.946
50+0.8450.97310.1630.899
Kort-geschoolden0.4380.2950.16310.563
Totaal_NWW0.9370.9460.8990.5631

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Allochtonen & PmAH & 50+ & Kort-geschoolden & Totaal_NWW \tabularnewline
Allochtonen & 1 & 0.895 & 0.845 & 0.438 & 0.937 \tabularnewline
PmAH & 0.895 & 1 & 0.973 & 0.295 & 0.946 \tabularnewline
50+ & 0.845 & 0.973 & 1 & 0.163 & 0.899 \tabularnewline
Kort-geschoolden & 0.438 & 0.295 & 0.163 & 1 & 0.563 \tabularnewline
Totaal_NWW & 0.937 & 0.946 & 0.899 & 0.563 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112846&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Allochtonen[/C][C]PmAH[/C][C]50+[/C][C]Kort-geschoolden[/C][C]Totaal_NWW[/C][/ROW]
[ROW][C]Allochtonen[/C][C]1[/C][C]0.895[/C][C]0.845[/C][C]0.438[/C][C]0.937[/C][/ROW]
[ROW][C]PmAH[/C][C]0.895[/C][C]1[/C][C]0.973[/C][C]0.295[/C][C]0.946[/C][/ROW]
[ROW][C]50+[/C][C]0.845[/C][C]0.973[/C][C]1[/C][C]0.163[/C][C]0.899[/C][/ROW]
[ROW][C]Kort-geschoolden[/C][C]0.438[/C][C]0.295[/C][C]0.163[/C][C]1[/C][C]0.563[/C][/ROW]
[ROW][C]Totaal_NWW[/C][C]0.937[/C][C]0.946[/C][C]0.899[/C][C]0.563[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112846&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112846&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=pearson)
AllochtonenPmAH50+Kort-geschooldenTotaal_NWW
Allochtonen10.8950.8450.4380.937
PmAH0.89510.9730.2950.946
50+0.8450.97310.1630.899
Kort-geschoolden0.4380.2950.16310.563
Totaal_NWW0.9370.9460.8990.5631






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Allochtonen;PmAH0.89520.89230.7307
p-value(0)(0)(0)
Allochtonen;50+0.84470.85810.7055
p-value(0)(0)(0)
Allochtonen;Kort-geschoolden0.43780.53210.3905
p-value(0)(0)(0)
Allochtonen;Totaal_NWW0.93740.95520.8288
p-value(0)(0)(0)
PmAH;50+0.9730.95260.8303
p-value(0)(0)(0)
PmAH;Kort-geschoolden0.29540.27070.2371
p-value(6e-04)(0.0018)(1e-04)
PmAH;Totaal_NWW0.94610.90460.7718
p-value(0)(0)(0)
50+;Kort-geschoolden0.16260.2010.2021
p-value(0.0635)(0.0215)(6e-04)
50+;Totaal_NWW0.89910.87560.7494
p-value(0)(0)(0)
Kort-geschoolden;Totaal_NWW0.56280.57730.4405
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
Allochtonen;PmAH & 0.8952 & 0.8923 & 0.7307 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Allochtonen;50+ & 0.8447 & 0.8581 & 0.7055 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Allochtonen;Kort-geschoolden & 0.4378 & 0.5321 & 0.3905 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Allochtonen;Totaal_NWW & 0.9374 & 0.9552 & 0.8288 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PmAH;50+ & 0.973 & 0.9526 & 0.8303 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PmAH;Kort-geschoolden & 0.2954 & 0.2707 & 0.2371 \tabularnewline
p-value & (6e-04) & (0.0018) & (1e-04) \tabularnewline
PmAH;Totaal_NWW & 0.9461 & 0.9046 & 0.7718 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
50+;Kort-geschoolden & 0.1626 & 0.201 & 0.2021 \tabularnewline
p-value & (0.0635) & (0.0215) & (6e-04) \tabularnewline
50+;Totaal_NWW & 0.8991 & 0.8756 & 0.7494 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Kort-geschoolden;Totaal_NWW & 0.5628 & 0.5773 & 0.4405 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112846&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]Allochtonen;PmAH[/C][C]0.8952[/C][C]0.8923[/C][C]0.7307[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Allochtonen;50+[/C][C]0.8447[/C][C]0.8581[/C][C]0.7055[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Allochtonen;Kort-geschoolden[/C][C]0.4378[/C][C]0.5321[/C][C]0.3905[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Allochtonen;Totaal_NWW[/C][C]0.9374[/C][C]0.9552[/C][C]0.8288[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PmAH;50+[/C][C]0.973[/C][C]0.9526[/C][C]0.8303[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PmAH;Kort-geschoolden[/C][C]0.2954[/C][C]0.2707[/C][C]0.2371[/C][/ROW]
[ROW][C]p-value[/C][C](6e-04)[/C][C](0.0018)[/C][C](1e-04)[/C][/ROW]
[ROW][C]PmAH;Totaal_NWW[/C][C]0.9461[/C][C]0.9046[/C][C]0.7718[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]50+;Kort-geschoolden[/C][C]0.1626[/C][C]0.201[/C][C]0.2021[/C][/ROW]
[ROW][C]p-value[/C][C](0.0635)[/C][C](0.0215)[/C][C](6e-04)[/C][/ROW]
[ROW][C]50+;Totaal_NWW[/C][C]0.8991[/C][C]0.8756[/C][C]0.7494[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Kort-geschoolden;Totaal_NWW[/C][C]0.5628[/C][C]0.5773[/C][C]0.4405[/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=112846&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112846&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
Allochtonen;PmAH0.89520.89230.7307
p-value(0)(0)(0)
Allochtonen;50+0.84470.85810.7055
p-value(0)(0)(0)
Allochtonen;Kort-geschoolden0.43780.53210.3905
p-value(0)(0)(0)
Allochtonen;Totaal_NWW0.93740.95520.8288
p-value(0)(0)(0)
PmAH;50+0.9730.95260.8303
p-value(0)(0)(0)
PmAH;Kort-geschoolden0.29540.27070.2371
p-value(6e-04)(0.0018)(1e-04)
PmAH;Totaal_NWW0.94610.90460.7718
p-value(0)(0)(0)
50+;Kort-geschoolden0.16260.2010.2021
p-value(0.0635)(0.0215)(6e-04)
50+;Totaal_NWW0.89910.87560.7494
p-value(0)(0)(0)
Kort-geschoolden;Totaal_NWW0.56280.57730.4405
p-value(0)(0)(0)


Figures (Output of Computation)

Input Parameters & R Code

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')