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Patrick.Wessarwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Sat, 18 Dec 2010 19:47:14 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/18/t1292701513cxgxmtff047rbme.htm/, Retrieved Tue, 30 Apr 2024 02:28:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112178, Retrieved Tue, 30 Apr 2024 02:28:18 +0000

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179

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-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
-   PD  [Kendall tau Correlation Matrix] [WS10] [2010-12-12 14:43:38] [87116ee6ef949037dfa02b8eb1a3bf97]
-   PD      [Kendall tau Correlation Matrix] [Pearson Correlation] [2010-12-18 19:47:14] [66b4703b90a9701067ac75b10c82aca9] [Current]

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Dataseries X:

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14	11	11	26	9	2	1	1
18	12	8	20	9	1	1	1
11	15	12	21	9	4	1	1
12	10	10	31	14	1	1	2
16	12	7	21	8	5	2	1
18	11	6	18	8	1	1	1
14	5	8	26	11	1	1	1
14	16	16	22	10	1	1	1
15	11	8	22	9	1	1	1
15	15	16	29	15	1	1	1
17	12	7	15	14	2	1	2
19	9	11	16	11	1	1	1
10	11	16	24	14	3	2	2
18	15	16	17	6	1	1	1
14	12	12	19	20	1	1	2
14	16	13	22	9	1	1	2
17	14	19	31	10	1	1	1
14	11	7	28	8	1	1	2
16	10	8	38	11	2	1	1
18	7	12	26	14	4	2	2
14	11	13	25	11	1	1	1
12	10	11	25	16	2	1	1
17	11	8	29	14	1	1	2
9	16	16	28	11	2	4	1
16	14	15	15	11	3	1	2
14	12	11	18	12	1	1	1
11	12	12	21	9	1	2	2
16	11	7	25	7	1	2	1
13	6	9	23	13	1	1	2
17	14	15	23	10	1	1	1
15	9	6	19	9	2	1	1
14	15	14	18	9	1	1	2
16	12	14	18	13	1	1	2
9	12	7	26	16	1	1	2
15	9	15	18	12	1	1	2
17	13	14	18	6	1	1	1
13	15	17	28	14	1	1	2
15	11	14	17	14	1	1	2
16	10	5	29	10	2	2	1
16	13	14	12	4	1	1	2
12	16	8	28	12	1	1	1
11	13	8	20	14	1	1	1
15	14	13	17	9	2	1	1
17	14	14	17	9	1	1	1
13	16	16	20	10	1	1	2
16	9	11	31	14	1	1	1
14	8	10	21	10	1	1	2
11	8	10	19	9	1	1	2
12	12	10	23	14	1	1	1
12	10	8	15	8	4	1	2
15	16	14	24	9	2	1	1
16	13	14	28	8	1	1	1
15	11	12	16	9	1	1	1
12	14	13	19	9	4	3	2
12	15	5	21	9	2	2	1
8	8	10	21	15	1	1	2
13	9	6	20	8	1	1	2
11	17	15	16	10	1	1	1
14	9	12	25	8	1	1	1
15	13	16	30	14	1	1	1
10	6	15	29	11	1	1	2
11	13	12	22	10	2	1	1
12	8	8	19	12	1	1	2
15	12	14	33	14	1	1	1
15	13	14	17	9	2	1	2
14	14	13	9	13	1	1	2
16	11	12	14	15	2	2	1
15	15	15	15	8	2	1	1
15	7	8	12	7	4	1	2
13	16	16	21	10	1	1	2
17	16	14	20	10	1	1	1
13	14	13	29	13	3	2	1
15	11	15	33	11	1	1	2
13	13	7	21	8	1	1	2
15	13	5	15	12	1	1	2
16	7	7	19	9	1	1	2
15	15	13	23	10	1	1	1
16	11	14	20	11	1	1	2
15	15	14	20	11	1	1	1
14	13	13	18	10	1	1	1
15	11	11	31	16	4	1	2
7	12	15	18	16	1	1	1
17	10	13	13	8	1	1	1
13	12	14	9	6	2	1	1
15	12	13	20	11	1	1	1
14	12	9	18	12	1	1	1
13	14	8	23	14	1	2	1
16	6	6	17	9	1	1	1
12	14	13	17	11	1	1	1
14	15	16	16	8	1	1	1
17	8	7	31	8	1	1	2
15	12	11	15	7	1	1	2
17	10	8	28	16	1	1	1
12	15	13	26	13	1	1	2
16	11	5	20	8	1	2	1
11	9	8	19	11	1	2	2
15	14	10	25	14	5	1	1
9	10	9	18	10	1	1	2
16	16	16	20	10	1	1	1
10	5	4	33	14	1	1	2
10	8	4	24	14	3	3	1
15	13	11	22	10	1	1	1
11	16	14	32	12	1	1	1
13	16	15	31	9	1	1	1
14	14	17	13	16	1	1	2
18	14	10	18	8	1	1	1
16	10	15	17	9	1	1	2
14	9	11	29	16	1	1	1
14	14	15	22	13	2	1	1
14	8	10	18	13	4	1	1
14	8	9	22	8	4	3	1
12	16	14	25	14	1	1	1
14	12	15	20	11	1	1	1
15	9	9	20	9	1	1	1
15	15	12	17	8	4	3	1
13	12	10	26	13	2	3	1
17	14	16	10	10	1	1	2
17	12	15	15	8	1	2	1
19	16	14	20	7	1	1	1
15	12	12	14	11	1	1	1
13	14	15	16	11	1	1	2
9	8	9	23	14	1	2	2
15	15	12	11	6	2	2	1
15	16	15	19	10	4	1	2
16	12	6	30	9	4	1	1
11	4	4	21	12	1	1	2
14	8	8	20	11	1	1	2
11	11	10	22	14	1	1	1
15	4	6	30	12	2	3	1
13	14	12	25	14	1	1	2
16	14	14	23	14	1	1	2
14	13	11	23	8	3	1	1
15	14	15	21	11	2	1	2
16	7	13	30	12	2	1	1
16	19	15	22	9	1	1	1
11	12	16	32	16	1	1	2
13	10	4	22	11	2	2	1
16	14	15	15	11	3	1	2
12	16	12	21	12	1	1	1
9	11	15	27	15	1	1	1
13	16	15	22	13	1	2	1
13	12	14	9	6	2	1	1
14	12	14	29	11	2	1	1
19	16	14	20	7	1	1	1
13	12	11	16	8	1	1	1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112178&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]6 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=112178&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112178&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Correlations for all pairs of data series (method=pearson)
	Happiness	Popularity	KnowingPeople	CMistakes	DAction	Tobacco	Drugs	Gender
Happiness	1	0.096	0.076	-0.143	-0.356	0.02	-0.166	-0.176
Popularity	0.096	1	0.573	-0.145	-0.14	-0.037	-0.067	-0.212
KnowingPeople	0.076	0.573	1	-0.103	0.011	-0.126	-0.181	-0.014
CMistakes	-0.143	-0.145	-0.103	1	0.38	-0.01	0.077	-0.099
DAction	-0.356	-0.14	0.011	0.38	1	-0.066	-0.017	0.163
Tobacco	0.02	-0.037	-0.126	-0.01	-0.066	1	0.364	-0.04
Drugs	-0.166	-0.067	-0.181	0.077	-0.017	0.364	1	-0.139
Gender	-0.176	-0.212	-0.014	-0.099	0.163	-0.04	-0.139	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Happiness & Popularity & KnowingPeople & CMistakes & DAction & Tobacco & Drugs & Gender \tabularnewline
Happiness & 1 & 0.096 & 0.076 & -0.143 & -0.356 & 0.02 & -0.166 & -0.176 \tabularnewline
Popularity & 0.096 & 1 & 0.573 & -0.145 & -0.14 & -0.037 & -0.067 & -0.212 \tabularnewline
KnowingPeople & 0.076 & 0.573 & 1 & -0.103 & 0.011 & -0.126 & -0.181 & -0.014 \tabularnewline
CMistakes & -0.143 & -0.145 & -0.103 & 1 & 0.38 & -0.01 & 0.077 & -0.099 \tabularnewline
DAction & -0.356 & -0.14 & 0.011 & 0.38 & 1 & -0.066 & -0.017 & 0.163 \tabularnewline
Tobacco & 0.02 & -0.037 & -0.126 & -0.01 & -0.066 & 1 & 0.364 & -0.04 \tabularnewline
Drugs & -0.166 & -0.067 & -0.181 & 0.077 & -0.017 & 0.364 & 1 & -0.139 \tabularnewline
Gender & -0.176 & -0.212 & -0.014 & -0.099 & 0.163 & -0.04 & -0.139 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112178&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Happiness[/C][C]Popularity[/C][C]KnowingPeople[/C][C]CMistakes[/C][C]DAction[/C][C]Tobacco[/C][C]Drugs[/C][C]Gender[/C][/ROW]
[ROW][C]Happiness[/C][C]1[/C][C]0.096[/C][C]0.076[/C][C]-0.143[/C][C]-0.356[/C][C]0.02[/C][C]-0.166[/C][C]-0.176[/C][/ROW]
[ROW][C]Popularity[/C][C]0.096[/C][C]1[/C][C]0.573[/C][C]-0.145[/C][C]-0.14[/C][C]-0.037[/C][C]-0.067[/C][C]-0.212[/C][/ROW]
[ROW][C]KnowingPeople[/C][C]0.076[/C][C]0.573[/C][C]1[/C][C]-0.103[/C][C]0.011[/C][C]-0.126[/C][C]-0.181[/C][C]-0.014[/C][/ROW]
[ROW][C]CMistakes[/C][C]-0.143[/C][C]-0.145[/C][C]-0.103[/C][C]1[/C][C]0.38[/C][C]-0.01[/C][C]0.077[/C][C]-0.099[/C][/ROW]
[ROW][C]DAction[/C][C]-0.356[/C][C]-0.14[/C][C]0.011[/C][C]0.38[/C][C]1[/C][C]-0.066[/C][C]-0.017[/C][C]0.163[/C][/ROW]
[ROW][C]Tobacco[/C][C]0.02[/C][C]-0.037[/C][C]-0.126[/C][C]-0.01[/C][C]-0.066[/C][C]1[/C][C]0.364[/C][C]-0.04[/C][/ROW]
[ROW][C]Drugs[/C][C]-0.166[/C][C]-0.067[/C][C]-0.181[/C][C]0.077[/C][C]-0.017[/C][C]0.364[/C][C]1[/C][C]-0.139[/C][/ROW]
[ROW][C]Gender[/C][C]-0.176[/C][C]-0.212[/C][C]-0.014[/C][C]-0.099[/C][C]0.163[/C][C]-0.04[/C][C]-0.139[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112178&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112178&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)
	Happiness	Popularity	KnowingPeople	CMistakes	DAction	Tobacco	Drugs	Gender
Happiness	1	0.096	0.076	-0.143	-0.356	0.02	-0.166	-0.176
Popularity	0.096	1	0.573	-0.145	-0.14	-0.037	-0.067	-0.212
KnowingPeople	0.076	0.573	1	-0.103	0.011	-0.126	-0.181	-0.014
CMistakes	-0.143	-0.145	-0.103	1	0.38	-0.01	0.077	-0.099
DAction	-0.356	-0.14	0.011	0.38	1	-0.066	-0.017	0.163
Tobacco	0.02	-0.037	-0.126	-0.01	-0.066	1	0.364	-0.04
Drugs	-0.166	-0.067	-0.181	0.077	-0.017	0.364	1	-0.139
Gender	-0.176	-0.212	-0.014	-0.099	0.163	-0.04	-0.139	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Happiness;Popularity	0.0959	0.0331	0.0201
p-value	(0.2511)	(0.6923)	(0.7452)
Happiness;KnowingPeople	0.0756	0.0621	0.053
p-value	(0.3661)	(0.4579)	(0.3884)
Happiness;CMistakes	-0.1434	-0.1797	-0.1288
p-value	(0.0854)	(0.0305)	(0.0333)
Happiness;DAction	-0.3559	-0.3326	-0.2573
p-value	(0)	(0)	(0)
Happiness;Tobacco	0.0196	0.0012	0.0015
p-value	(0.815)	(0.9887)	(0.9829)
Happiness;Drugs	-0.1664	-0.1149	-0.0978
p-value	(0.0454)	(0.1687)	(0.1673)
Happiness;Gender	-0.176	-0.163	-0.1409
p-value	(0.0343)	(0.0502)	(0.0505)
Popularity;KnowingPeople	0.5725	0.5752	0.4366
p-value	(0)	(0)	(0)
Popularity;CMistakes	-0.1453	-0.113	-0.0803
p-value	(0.0812)	(0.176)	(0.1808)
Popularity;DAction	-0.1396	-0.1353	-0.0984
p-value	(0.094)	(0.1046)	(0.1098)
Popularity;Tobacco	-0.0367	-0.032	-0.0258
p-value	(0.6613)	(0.702)	(0.7062)
Popularity;Drugs	-0.0671	-0.0783	-0.0668
p-value	(0.4224)	(0.3495)	(0.341)
Popularity;Gender	-0.2121	-0.2018	-0.1729
p-value	(0.0104)	(0.0149)	(0.0155)
KnowingPeople;CMistakes	-0.1029	-0.0991	-0.075
p-value	(0.2181)	(0.2355)	(0.2087)
KnowingPeople;DAction	0.0106	0.034	0.0235
p-value	(0.8997)	(0.685)	(0.7006)
KnowingPeople;Tobacco	-0.1257	-0.1184	-0.0981
p-value	(0.1319)	(0.156)	(0.1494)
KnowingPeople;Drugs	-0.1813	-0.203	-0.1699
p-value	(0.0291)	(0.0143)	(0.0149)
KnowingPeople;Gender	-0.0141	0.0046	0.0039
p-value	(0.8666)	(0.9563)	(0.9561)
CMistakes;DAction	0.3799	0.386	0.2905
p-value	(0)	(0)	(0)
CMistakes;Tobacco	-0.01	0.0022	0.0024
p-value	(0.905)	(0.9787)	(0.9711)
CMistakes;Drugs	0.077	0.0861	0.0726
p-value	(0.3574)	(0.3032)	(0.2905)
CMistakes;Gender	-0.0994	-0.1093	-0.0917
p-value	(0.2344)	(0.1905)	(0.1895)
DAction;Tobacco	-0.0664	-0.0798	-0.0657
p-value	(0.4275)	(0.3402)	(0.3389)
DAction;Drugs	-0.0169	-0.0184	-0.0162
p-value	(0.8403)	(0.8262)	(0.8183)
DAction;Gender	0.1625	0.1611	0.1387
p-value	(0.0508)	(0.0529)	(0.0532)
Tobacco;Drugs	0.3637	0.3794	0.3575
p-value	(0)	(0)	(0)
Tobacco;Gender	-0.0397	-0.1102	-0.1056
p-value	(0.6351)	(0.1868)	(0.1859)
Drugs;Gender	-0.1395	-0.1291	-0.1269
p-value	(0.0943)	(0.1216)	(0.1212)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Happiness;Popularity & 0.0959 & 0.0331 & 0.0201 \tabularnewline
p-value & (0.2511) & (0.6923) & (0.7452) \tabularnewline
Happiness;KnowingPeople & 0.0756 & 0.0621 & 0.053 \tabularnewline
p-value & (0.3661) & (0.4579) & (0.3884) \tabularnewline
Happiness;CMistakes & -0.1434 & -0.1797 & -0.1288 \tabularnewline
p-value & (0.0854) & (0.0305) & (0.0333) \tabularnewline
Happiness;DAction & -0.3559 & -0.3326 & -0.2573 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Happiness;Tobacco & 0.0196 & 0.0012 & 0.0015 \tabularnewline
p-value & (0.815) & (0.9887) & (0.9829) \tabularnewline
Happiness;Drugs & -0.1664 & -0.1149 & -0.0978 \tabularnewline
p-value & (0.0454) & (0.1687) & (0.1673) \tabularnewline
Happiness;Gender & -0.176 & -0.163 & -0.1409 \tabularnewline
p-value & (0.0343) & (0.0502) & (0.0505) \tabularnewline
Popularity;KnowingPeople & 0.5725 & 0.5752 & 0.4366 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Popularity;CMistakes & -0.1453 & -0.113 & -0.0803 \tabularnewline
p-value & (0.0812) & (0.176) & (0.1808) \tabularnewline
Popularity;DAction & -0.1396 & -0.1353 & -0.0984 \tabularnewline
p-value & (0.094) & (0.1046) & (0.1098) \tabularnewline
Popularity;Tobacco & -0.0367 & -0.032 & -0.0258 \tabularnewline
p-value & (0.6613) & (0.702) & (0.7062) \tabularnewline
Popularity;Drugs & -0.0671 & -0.0783 & -0.0668 \tabularnewline
p-value & (0.4224) & (0.3495) & (0.341) \tabularnewline
Popularity;Gender & -0.2121 & -0.2018 & -0.1729 \tabularnewline
p-value & (0.0104) & (0.0149) & (0.0155) \tabularnewline
KnowingPeople;CMistakes & -0.1029 & -0.0991 & -0.075 \tabularnewline
p-value & (0.2181) & (0.2355) & (0.2087) \tabularnewline
KnowingPeople;DAction & 0.0106 & 0.034 & 0.0235 \tabularnewline
p-value & (0.8997) & (0.685) & (0.7006) \tabularnewline
KnowingPeople;Tobacco & -0.1257 & -0.1184 & -0.0981 \tabularnewline
p-value & (0.1319) & (0.156) & (0.1494) \tabularnewline
KnowingPeople;Drugs & -0.1813 & -0.203 & -0.1699 \tabularnewline
p-value & (0.0291) & (0.0143) & (0.0149) \tabularnewline
KnowingPeople;Gender & -0.0141 & 0.0046 & 0.0039 \tabularnewline
p-value & (0.8666) & (0.9563) & (0.9561) \tabularnewline
CMistakes;DAction & 0.3799 & 0.386 & 0.2905 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CMistakes;Tobacco & -0.01 & 0.0022 & 0.0024 \tabularnewline
p-value & (0.905) & (0.9787) & (0.9711) \tabularnewline
CMistakes;Drugs & 0.077 & 0.0861 & 0.0726 \tabularnewline
p-value & (0.3574) & (0.3032) & (0.2905) \tabularnewline
CMistakes;Gender & -0.0994 & -0.1093 & -0.0917 \tabularnewline
p-value & (0.2344) & (0.1905) & (0.1895) \tabularnewline
DAction;Tobacco & -0.0664 & -0.0798 & -0.0657 \tabularnewline
p-value & (0.4275) & (0.3402) & (0.3389) \tabularnewline
DAction;Drugs & -0.0169 & -0.0184 & -0.0162 \tabularnewline
p-value & (0.8403) & (0.8262) & (0.8183) \tabularnewline
DAction;Gender & 0.1625 & 0.1611 & 0.1387 \tabularnewline
p-value & (0.0508) & (0.0529) & (0.0532) \tabularnewline
Tobacco;Drugs & 0.3637 & 0.3794 & 0.3575 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tobacco;Gender & -0.0397 & -0.1102 & -0.1056 \tabularnewline
p-value & (0.6351) & (0.1868) & (0.1859) \tabularnewline
Drugs;Gender & -0.1395 & -0.1291 & -0.1269 \tabularnewline
p-value & (0.0943) & (0.1216) & (0.1212) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112178&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]Happiness;Popularity[/C][C]0.0959[/C][C]0.0331[/C][C]0.0201[/C][/ROW]
[ROW][C]p-value[/C][C](0.2511)[/C][C](0.6923)[/C][C](0.7452)[/C][/ROW]
[ROW][C]Happiness;KnowingPeople[/C][C]0.0756[/C][C]0.0621[/C][C]0.053[/C][/ROW]
[ROW][C]p-value[/C][C](0.3661)[/C][C](0.4579)[/C][C](0.3884)[/C][/ROW]
[ROW][C]Happiness;CMistakes[/C][C]-0.1434[/C][C]-0.1797[/C][C]-0.1288[/C][/ROW]
[ROW][C]p-value[/C][C](0.0854)[/C][C](0.0305)[/C][C](0.0333)[/C][/ROW]
[ROW][C]Happiness;DAction[/C][C]-0.3559[/C][C]-0.3326[/C][C]-0.2573[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Happiness;Tobacco[/C][C]0.0196[/C][C]0.0012[/C][C]0.0015[/C][/ROW]
[ROW][C]p-value[/C][C](0.815)[/C][C](0.9887)[/C][C](0.9829)[/C][/ROW]
[ROW][C]Happiness;Drugs[/C][C]-0.1664[/C][C]-0.1149[/C][C]-0.0978[/C][/ROW]
[ROW][C]p-value[/C][C](0.0454)[/C][C](0.1687)[/C][C](0.1673)[/C][/ROW]
[ROW][C]Happiness;Gender[/C][C]-0.176[/C][C]-0.163[/C][C]-0.1409[/C][/ROW]
[ROW][C]p-value[/C][C](0.0343)[/C][C](0.0502)[/C][C](0.0505)[/C][/ROW]
[ROW][C]Popularity;KnowingPeople[/C][C]0.5725[/C][C]0.5752[/C][C]0.4366[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Popularity;CMistakes[/C][C]-0.1453[/C][C]-0.113[/C][C]-0.0803[/C][/ROW]
[ROW][C]p-value[/C][C](0.0812)[/C][C](0.176)[/C][C](0.1808)[/C][/ROW]
[ROW][C]Popularity;DAction[/C][C]-0.1396[/C][C]-0.1353[/C][C]-0.0984[/C][/ROW]
[ROW][C]p-value[/C][C](0.094)[/C][C](0.1046)[/C][C](0.1098)[/C][/ROW]
[ROW][C]Popularity;Tobacco[/C][C]-0.0367[/C][C]-0.032[/C][C]-0.0258[/C][/ROW]
[ROW][C]p-value[/C][C](0.6613)[/C][C](0.702)[/C][C](0.7062)[/C][/ROW]
[ROW][C]Popularity;Drugs[/C][C]-0.0671[/C][C]-0.0783[/C][C]-0.0668[/C][/ROW]
[ROW][C]p-value[/C][C](0.4224)[/C][C](0.3495)[/C][C](0.341)[/C][/ROW]
[ROW][C]Popularity;Gender[/C][C]-0.2121[/C][C]-0.2018[/C][C]-0.1729[/C][/ROW]
[ROW][C]p-value[/C][C](0.0104)[/C][C](0.0149)[/C][C](0.0155)[/C][/ROW]
[ROW][C]KnowingPeople;CMistakes[/C][C]-0.1029[/C][C]-0.0991[/C][C]-0.075[/C][/ROW]
[ROW][C]p-value[/C][C](0.2181)[/C][C](0.2355)[/C][C](0.2087)[/C][/ROW]
[ROW][C]KnowingPeople;DAction[/C][C]0.0106[/C][C]0.034[/C][C]0.0235[/C][/ROW]
[ROW][C]p-value[/C][C](0.8997)[/C][C](0.685)[/C][C](0.7006)[/C][/ROW]
[ROW][C]KnowingPeople;Tobacco[/C][C]-0.1257[/C][C]-0.1184[/C][C]-0.0981[/C][/ROW]
[ROW][C]p-value[/C][C](0.1319)[/C][C](0.156)[/C][C](0.1494)[/C][/ROW]
[ROW][C]KnowingPeople;Drugs[/C][C]-0.1813[/C][C]-0.203[/C][C]-0.1699[/C][/ROW]
[ROW][C]p-value[/C][C](0.0291)[/C][C](0.0143)[/C][C](0.0149)[/C][/ROW]
[ROW][C]KnowingPeople;Gender[/C][C]-0.0141[/C][C]0.0046[/C][C]0.0039[/C][/ROW]
[ROW][C]p-value[/C][C](0.8666)[/C][C](0.9563)[/C][C](0.9561)[/C][/ROW]
[ROW][C]CMistakes;DAction[/C][C]0.3799[/C][C]0.386[/C][C]0.2905[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CMistakes;Tobacco[/C][C]-0.01[/C][C]0.0022[/C][C]0.0024[/C][/ROW]
[ROW][C]p-value[/C][C](0.905)[/C][C](0.9787)[/C][C](0.9711)[/C][/ROW]
[ROW][C]CMistakes;Drugs[/C][C]0.077[/C][C]0.0861[/C][C]0.0726[/C][/ROW]
[ROW][C]p-value[/C][C](0.3574)[/C][C](0.3032)[/C][C](0.2905)[/C][/ROW]
[ROW][C]CMistakes;Gender[/C][C]-0.0994[/C][C]-0.1093[/C][C]-0.0917[/C][/ROW]
[ROW][C]p-value[/C][C](0.2344)[/C][C](0.1905)[/C][C](0.1895)[/C][/ROW]
[ROW][C]DAction;Tobacco[/C][C]-0.0664[/C][C]-0.0798[/C][C]-0.0657[/C][/ROW]
[ROW][C]p-value[/C][C](0.4275)[/C][C](0.3402)[/C][C](0.3389)[/C][/ROW]
[ROW][C]DAction;Drugs[/C][C]-0.0169[/C][C]-0.0184[/C][C]-0.0162[/C][/ROW]
[ROW][C]p-value[/C][C](0.8403)[/C][C](0.8262)[/C][C](0.8183)[/C][/ROW]
[ROW][C]DAction;Gender[/C][C]0.1625[/C][C]0.1611[/C][C]0.1387[/C][/ROW]
[ROW][C]p-value[/C][C](0.0508)[/C][C](0.0529)[/C][C](0.0532)[/C][/ROW]
[ROW][C]Tobacco;Drugs[/C][C]0.3637[/C][C]0.3794[/C][C]0.3575[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tobacco;Gender[/C][C]-0.0397[/C][C]-0.1102[/C][C]-0.1056[/C][/ROW]
[ROW][C]p-value[/C][C](0.6351)[/C][C](0.1868)[/C][C](0.1859)[/C][/ROW]
[ROW][C]Drugs;Gender[/C][C]-0.1395[/C][C]-0.1291[/C][C]-0.1269[/C][/ROW]
[ROW][C]p-value[/C][C](0.0943)[/C][C](0.1216)[/C][C](0.1212)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112178&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112178&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
pair	Pearson r	Spearman rho	Kendall tau
Happiness;Popularity	0.0959	0.0331	0.0201
p-value	(0.2511)	(0.6923)	(0.7452)
Happiness;KnowingPeople	0.0756	0.0621	0.053
p-value	(0.3661)	(0.4579)	(0.3884)
Happiness;CMistakes	-0.1434	-0.1797	-0.1288
p-value	(0.0854)	(0.0305)	(0.0333)
Happiness;DAction	-0.3559	-0.3326	-0.2573
p-value	(0)	(0)	(0)
Happiness;Tobacco	0.0196	0.0012	0.0015
p-value	(0.815)	(0.9887)	(0.9829)
Happiness;Drugs	-0.1664	-0.1149	-0.0978
p-value	(0.0454)	(0.1687)	(0.1673)
Happiness;Gender	-0.176	-0.163	-0.1409
p-value	(0.0343)	(0.0502)	(0.0505)
Popularity;KnowingPeople	0.5725	0.5752	0.4366
p-value	(0)	(0)	(0)
Popularity;CMistakes	-0.1453	-0.113	-0.0803
p-value	(0.0812)	(0.176)	(0.1808)
Popularity;DAction	-0.1396	-0.1353	-0.0984
p-value	(0.094)	(0.1046)	(0.1098)
Popularity;Tobacco	-0.0367	-0.032	-0.0258
p-value	(0.6613)	(0.702)	(0.7062)
Popularity;Drugs	-0.0671	-0.0783	-0.0668
p-value	(0.4224)	(0.3495)	(0.341)
Popularity;Gender	-0.2121	-0.2018	-0.1729
p-value	(0.0104)	(0.0149)	(0.0155)
KnowingPeople;CMistakes	-0.1029	-0.0991	-0.075
p-value	(0.2181)	(0.2355)	(0.2087)
KnowingPeople;DAction	0.0106	0.034	0.0235
p-value	(0.8997)	(0.685)	(0.7006)
KnowingPeople;Tobacco	-0.1257	-0.1184	-0.0981
p-value	(0.1319)	(0.156)	(0.1494)
KnowingPeople;Drugs	-0.1813	-0.203	-0.1699
p-value	(0.0291)	(0.0143)	(0.0149)
KnowingPeople;Gender	-0.0141	0.0046	0.0039
p-value	(0.8666)	(0.9563)	(0.9561)
CMistakes;DAction	0.3799	0.386	0.2905
p-value	(0)	(0)	(0)
CMistakes;Tobacco	-0.01	0.0022	0.0024
p-value	(0.905)	(0.9787)	(0.9711)
CMistakes;Drugs	0.077	0.0861	0.0726
p-value	(0.3574)	(0.3032)	(0.2905)
CMistakes;Gender	-0.0994	-0.1093	-0.0917
p-value	(0.2344)	(0.1905)	(0.1895)
DAction;Tobacco	-0.0664	-0.0798	-0.0657
p-value	(0.4275)	(0.3402)	(0.3389)
DAction;Drugs	-0.0169	-0.0184	-0.0162
p-value	(0.8403)	(0.8262)	(0.8183)
DAction;Gender	0.1625	0.1611	0.1387
p-value	(0.0508)	(0.0529)	(0.0532)
Tobacco;Drugs	0.3637	0.3794	0.3575
p-value	(0)	(0)	(0)
Tobacco;Gender	-0.0397	-0.1102	-0.1056
p-value	(0.6351)	(0.1868)	(0.1859)
Drugs;Gender	-0.1395	-0.1291	-0.1269
p-value	(0.0943)	(0.1216)	(0.1212)

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code