Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Mon, 10 Dec 2012 11:46:02 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/10/t1355158012h7or82s35qvmdsd.htm/, Retrieved Fri, 26 Apr 2024 08:38:27 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198240, Retrieved Fri, 26 Apr 2024 08:38:27 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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]
- RMPD    [Kendall tau Correlation Matrix] [WS 10, Pearson Co...] [2012-12-10 16:46:02] [e4c351aee2a0bb2c047702ea90f356fa] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

2	7	41	38	13	12	14	12	53
2	5	39	32	16	11	18	11	86
2	5	30	35	19	15	11	14	66
1	5	31	33	15	6	12	12	67
2	8	34	37	14	13	16	21	76
2	6	35	29	13	10	18	12	78
2	5	39	31	19	12	14	22	53
2	6	34	36	15	14	14	11	80
2	5	36	35	14	12	15	10	74
2	4	37	38	15	6	15	13	76
1	6	38	31	16	10	17	10	79
2	5	36	34	16	12	19	8	54
1	5	38	35	16	12	10	15	67
2	6	39	38	16	11	16	14	54
2	7	33	37	17	15	18	10	87
1	6	32	33	15	12	14	14	58
1	7	36	32	15	10	14	14	75
2	6	38	38	20	12	17	11	88
1	8	39	38	18	11	14	10	64
2	7	32	32	16	12	16	13	57
1	5	32	33	16	11	18	7	66
2	5	31	31	16	12	11	14	68
2	7	39	38	19	13	14	12	54
2	7	37	39	16	11	12	14	56
1	5	39	32	17	9	17	11	86
2	4	41	32	17	13	9	9	80
1	10	36	35	16	10	16	11	76
2	6	33	37	15	14	14	15	69
2	5	33	33	16	12	15	14	78
1	5	34	33	14	10	11	13	67
2	5	31	28	15	12	16	9	80
1	5	27	32	12	8	13	15	54
2	6	37	31	14	10	17	10	71
2	5	34	37	16	12	15	11	84
1	5	34	30	14	12	14	13	74
1	5	32	33	7	7	16	8	71
1	5	29	31	10	6	9	20	63
1	5	36	33	14	12	15	12	71
2	5	29	31	16	10	17	10	76
1	5	35	33	16	10	13	10	69
1	5	37	32	16	10	15	9	74
2	7	34	33	14	12	16	14	75
1	5	38	32	20	15	16	8	54
1	6	35	33	14	10	12	14	52
2	7	38	28	14	10	12	11	69
2	7	37	35	11	12	11	13	68
2	5	38	39	14	13	15	9	65
2	5	33	34	15	11	15	11	75
2	4	36	38	16	11	17	15	74
1	5	38	32	14	12	13	11	75
2	4	32	38	16	14	16	10	72
1	5	32	30	14	10	14	14	67
1	5	32	33	12	12	11	18	63
2	7	34	38	16	13	12	14	62
1	5	32	32	9	5	12	11	63
2	5	37	32	14	6	15	12	76
2	6	39	34	16	12	16	13	74
2	4	29	34	16	12	15	9	67
1	6	37	36	15	11	12	10	73
2	6	35	34	16	10	12	15	70
1	5	30	28	12	7	8	20	53
1	7	38	34	16	12	13	12	77
2	6	34	35	16	14	11	12	77
2	8	31	35	14	11	14	14	52
2	7	34	31	16	12	15	13	54
1	5	35	37	17	13	10	11	80
2	6	36	35	18	14	11	17	66
1	6	30	27	18	11	12	12	73
2	5	39	40	12	12	15	13	63
1	5	35	37	16	12	15	14	69
1	5	38	36	10	8	14	13	67
2	5	31	38	14	11	16	15	54
2	4	34	39	18	14	15	13	81
1	6	38	41	18	14	15	10	69
1	6	34	27	16	12	13	11	84
2	6	39	30	17	9	12	19	80
2	6	37	37	16	13	17	13	70
2	7	34	31	16	11	13	17	69
1	5	28	31	13	12	15	13	77
1	7	37	27	16	12	13	9	54
1	6	33	36	16	12	15	11	79
1	5	37	38	20	12	16	10	30
2	5	35	37	16	12	15	9	71
1	4	37	33	15	12	16	12	73
2	8	32	34	15	11	15	12	72
2	8	33	31	16	10	14	13	77
1	5	38	39	14	9	15	13	75
2	5	33	34	16	12	14	12	69
2	6	29	32	16	12	13	15	54
2	4	33	33	15	12	7	22	70
2	5	31	36	12	9	17	13	73
2	5	36	32	17	15	13	15	54
2	5	35	41	16	12	15	13	77
2	5	32	28	15	12	14	15	82
2	6	29	30	13	12	13	10	80
2	6	39	36	16	10	16	11	80
2	5	37	35	16	13	12	16	69
2	6	35	31	16	9	14	11	78
1	5	37	34	16	12	17	11	81
1	7	32	36	14	10	15	10	76
2	5	38	36	16	14	17	10	76
1	6	37	35	16	11	12	16	73
2	6	36	37	20	15	16	12	85
1	6	32	28	15	11	11	11	66
2	4	33	39	16	11	15	16	79
1	5	40	32	13	12	9	19	68
2	5	38	35	17	12	16	11	76
1	7	41	39	16	12	15	16	71
1	6	36	35	16	11	10	15	54
2	9	43	42	12	7	10	24	46
2	6	30	34	16	12	15	14	82
2	6	31	33	16	14	11	15	74
2	5	32	41	17	11	13	11	88
1	6	32	33	13	11	14	15	38
2	5	37	34	12	10	18	12	76
1	8	37	32	18	13	16	10	86
2	7	33	40	14	13	14	14	54
2	5	34	40	14	8	14	13	70
2	7	33	35	13	11	14	9	69
2	6	38	36	16	12	14	15	90
2	6	33	37	13	11	12	15	54
2	9	31	27	16	13	14	14	76
2	7	38	39	13	12	15	11	89
2	6	37	38	16	14	15	8	76
2	5	33	31	15	13	15	11	73
2	5	31	33	16	15	13	11	79
1	6	39	32	15	10	17	8	90
2	6	44	39	17	11	17	10	74
2	7	33	36	15	9	19	11	81
2	5	35	33	12	11	15	13	72
1	5	32	33	16	10	13	11	71
1	5	28	32	10	11	9	20	66
2	6	40	37	16	8	15	10	77
1	4	27	30	12	11	15	15	65
1	5	37	38	14	12	15	12	74
2	7	32	29	15	12	16	14	82
1	5	28	22	13	9	11	23	54
1	7	34	35	15	11	14	14	63
2	7	30	35	11	10	11	16	54
2	6	35	34	12	8	15	11	64
1	5	31	35	8	9	13	12	69
2	8	32	34	16	8	15	10	54
1	5	30	34	15	9	16	14	84
2	5	30	35	17	15	14	12	86
1	5	31	23	16	11	15	12	77
2	6	40	31	10	8	16	11	89
2	4	32	27	18	13	16	12	76
1	5	36	36	13	12	11	13	60
1	5	32	31	16	12	12	11	75
1	7	35	32	13	9	9	19	73
2	6	38	39	10	7	16	12	85
2	7	42	37	15	13	13	17	79
1	10	34	38	16	9	16	9	71
2	6	35	39	16	6	12	12	72
2	8	35	34	14	8	9	19	69
2	4	33	31	10	8	13	18	78
2	5	36	32	17	15	13	15	54
2	6	32	37	13	6	14	14	69
2	7	33	36	15	9	19	11	81
2	7	34	32	16	11	13	9	84
2	6	32	35	12	8	12	18	84
2	6	34	36	13	8	13	16	69

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198240&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198240&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198240&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	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Correlations for all pairs of data series (method=pearson)
	Gender	Age	Connected	Separate	Learning	Software	Happiness	Depression	Belonging
Gender	1	0.079	0.064	0.24	0.119	0.163	0.182	0.045	0.143
Age	0.079	1	0.148	0.106	0.051	-0.06	0.017	0.031	-0.068
Connected	0.064	0.148	1	0.368	0.214	0.062	0.143	-0.12	0.081
Separate	0.24	0.106	0.368	1	0.08	0.068	0.154	-0.078	-0.023
Learning	0.119	0.051	0.214	0.08	1	0.546	0.183	-0.233	0.089
Software	0.163	-0.06	0.062	0.068	0.546	1	0.074	-0.135	0.038
Happiness	0.182	0.017	0.143	0.154	0.183	0.074	1	-0.544	0.286
Depression	0.045	0.031	-0.12	-0.078	-0.233	-0.135	-0.544	1	-0.274
Belonging	0.143	-0.068	0.081	-0.023	0.089	0.038	0.286	-0.274	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Gender & Age & Connected & Separate & Learning & Software & Happiness & Depression & Belonging \tabularnewline
Gender & 1 & 0.079 & 0.064 & 0.24 & 0.119 & 0.163 & 0.182 & 0.045 & 0.143 \tabularnewline
Age & 0.079 & 1 & 0.148 & 0.106 & 0.051 & -0.06 & 0.017 & 0.031 & -0.068 \tabularnewline
Connected & 0.064 & 0.148 & 1 & 0.368 & 0.214 & 0.062 & 0.143 & -0.12 & 0.081 \tabularnewline
Separate & 0.24 & 0.106 & 0.368 & 1 & 0.08 & 0.068 & 0.154 & -0.078 & -0.023 \tabularnewline
Learning & 0.119 & 0.051 & 0.214 & 0.08 & 1 & 0.546 & 0.183 & -0.233 & 0.089 \tabularnewline
Software & 0.163 & -0.06 & 0.062 & 0.068 & 0.546 & 1 & 0.074 & -0.135 & 0.038 \tabularnewline
Happiness & 0.182 & 0.017 & 0.143 & 0.154 & 0.183 & 0.074 & 1 & -0.544 & 0.286 \tabularnewline
Depression & 0.045 & 0.031 & -0.12 & -0.078 & -0.233 & -0.135 & -0.544 & 1 & -0.274 \tabularnewline
Belonging & 0.143 & -0.068 & 0.081 & -0.023 & 0.089 & 0.038 & 0.286 & -0.274 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198240&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]Age[/C][C]Connected[/C][C]Separate[/C][C]Learning[/C][C]Software[/C][C]Happiness[/C][C]Depression[/C][C]Belonging[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]0.079[/C][C]0.064[/C][C]0.24[/C][C]0.119[/C][C]0.163[/C][C]0.182[/C][C]0.045[/C][C]0.143[/C][/ROW]
[ROW][C]Age[/C][C]0.079[/C][C]1[/C][C]0.148[/C][C]0.106[/C][C]0.051[/C][C]-0.06[/C][C]0.017[/C][C]0.031[/C][C]-0.068[/C][/ROW]
[ROW][C]Connected[/C][C]0.064[/C][C]0.148[/C][C]1[/C][C]0.368[/C][C]0.214[/C][C]0.062[/C][C]0.143[/C][C]-0.12[/C][C]0.081[/C][/ROW]
[ROW][C]Separate[/C][C]0.24[/C][C]0.106[/C][C]0.368[/C][C]1[/C][C]0.08[/C][C]0.068[/C][C]0.154[/C][C]-0.078[/C][C]-0.023[/C][/ROW]
[ROW][C]Learning[/C][C]0.119[/C][C]0.051[/C][C]0.214[/C][C]0.08[/C][C]1[/C][C]0.546[/C][C]0.183[/C][C]-0.233[/C][C]0.089[/C][/ROW]
[ROW][C]Software[/C][C]0.163[/C][C]-0.06[/C][C]0.062[/C][C]0.068[/C][C]0.546[/C][C]1[/C][C]0.074[/C][C]-0.135[/C][C]0.038[/C][/ROW]
[ROW][C]Happiness[/C][C]0.182[/C][C]0.017[/C][C]0.143[/C][C]0.154[/C][C]0.183[/C][C]0.074[/C][C]1[/C][C]-0.544[/C][C]0.286[/C][/ROW]
[ROW][C]Depression[/C][C]0.045[/C][C]0.031[/C][C]-0.12[/C][C]-0.078[/C][C]-0.233[/C][C]-0.135[/C][C]-0.544[/C][C]1[/C][C]-0.274[/C][/ROW]
[ROW][C]Belonging[/C][C]0.143[/C][C]-0.068[/C][C]0.081[/C][C]-0.023[/C][C]0.089[/C][C]0.038[/C][C]0.286[/C][C]-0.274[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198240&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198240&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)
	Gender	Age	Connected	Separate	Learning	Software	Happiness	Depression	Belonging
Gender	1	0.079	0.064	0.24	0.119	0.163	0.182	0.045	0.143
Age	0.079	1	0.148	0.106	0.051	-0.06	0.017	0.031	-0.068
Connected	0.064	0.148	1	0.368	0.214	0.062	0.143	-0.12	0.081
Separate	0.24	0.106	0.368	1	0.08	0.068	0.154	-0.078	-0.023
Learning	0.119	0.051	0.214	0.08	1	0.546	0.183	-0.233	0.089
Software	0.163	-0.06	0.062	0.068	0.546	1	0.074	-0.135	0.038
Happiness	0.182	0.017	0.143	0.154	0.183	0.074	1	-0.544	0.286
Depression	0.045	0.031	-0.12	-0.078	-0.233	-0.135	-0.544	1	-0.274
Belonging	0.143	-0.068	0.081	-0.023	0.089	0.038	0.286	-0.274	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Gender;Age	0.0793	0.1255	0.1149
p-value	(0.3161)	(0.1116)	(0.1113)
Gender;Connected	0.0645	0.0357	0.0304
p-value	(0.4149)	(0.652)	(0.6505)
Gender;Separate	0.2398	0.2283	0.1941
p-value	(0.0021)	(0.0035)	(0.0038)
Gender;Learning	0.1189	0.1077	0.0948
p-value	(0.1319)	(0.1724)	(0.1717)
Gender;Software	0.1634	0.1898	0.166
p-value	(0.0377)	(0.0156)	(0.016)
Gender;Happiness	0.1818	0.1643	0.1422
p-value	(0.0206)	(0.0367)	(0.0371)
Gender;Depression	0.0448	0.0654	0.0561
p-value	(0.5711)	(0.4082)	(0.4065)
Gender;Belonging	0.1434	0.1689	0.1409
p-value	(0.0687)	(0.0317)	(0.0321)
Age;Connected	0.1478	0.1481	0.1122
p-value	(0.0606)	(0.0599)	(0.0675)
Age;Separate	0.1057	0.1124	0.0898
p-value	(0.1807)	(0.1544)	(0.1433)
Age;Learning	0.0506	0.0098	0.0075
p-value	(0.5228)	(0.9018)	(0.9065)
Age;Software	-0.0602	-0.0681	-0.0552
p-value	(0.4463)	(0.389)	(0.3822)
Age;Happiness	0.0166	-0.0337	-0.0235
p-value	(0.8337)	(0.6707)	(0.707)
Age;Depression	0.0309	0.0179	0.0133
p-value	(0.6964)	(0.8208)	(0.8298)
Age;Belonging	-0.0678	-0.0234	-0.0188
p-value	(0.3913)	(0.7675)	(0.7554)
Connected;Separate	0.3682	0.3243	0.2413
p-value	(0)	(0)	(0)
Connected;Learning	0.2137	0.2076	0.1586
p-value	(0.0063)	(0.008)	(0.0072)
Connected;Software	0.0622	0.0748	0.0549
p-value	(0.4317)	(0.3439)	(0.3491)
Connected;Happiness	0.1427	0.1717	0.1274
p-value	(0.0701)	(0.0289)	(0.0283)
Connected;Depression	-0.1203	-0.1676	-0.128
p-value	(0.1274)	(0.033)	(0.026)
Connected;Belonging	0.0805	0.0983	0.0718
p-value	(0.3083)	(0.2131)	(0.1997)
Separate;Learning	0.0796	0.0878	0.0665
p-value	(0.3139)	(0.2666)	(0.2597)
Separate;Software	0.0679	0.1111	0.0787
p-value	(0.3906)	(0.1594)	(0.1795)
Separate;Happiness	0.1537	0.1543	0.1097
p-value	(0.0509)	(0.05)	(0.0589)
Separate;Depression	-0.0783	-0.036	-0.0297
p-value	(0.3219)	(0.6492)	(0.606)
Separate;Belonging	-0.0226	-0.0219	-0.0142
p-value	(0.7752)	(0.7824)	(0.7999)
Learning;Software	0.5456	0.4881	0.3906
p-value	(0)	(0)	(0)
Learning;Happiness	0.1829	0.1553	0.1199
p-value	(0.0198)	(0.0484)	(0.0461)
Learning;Depression	-0.2327	-0.2515	-0.1892
p-value	(0.0029)	(0.0012)	(0.0015)
Learning;Belonging	0.089	0.1872	0.1468
p-value	(0.2601)	(0.017)	(0.0113)
Software;Happiness	0.074	0.0312	0.0241
p-value	(0.3492)	(0.6933)	(0.6863)
Software;Depression	-0.1349	-0.0649	-0.0499
p-value	(0.087)	(0.4121)	(0.3988)
Software;Belonging	0.038	0.0543	0.0389
p-value	(0.6309)	(0.4925)	(0.4996)
Happiness;Depression	-0.5442	-0.4738	-0.3724
p-value	(0)	(0)	(0)
Happiness;Belonging	0.2856	0.3618	0.2635
p-value	(2e-04)	(0)	(0)
Depression;Belonging	-0.274	-0.2906	-0.2136
p-value	(4e-04)	(2e-04)	(2e-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;Age & 0.0793 & 0.1255 & 0.1149 \tabularnewline
p-value & (0.3161) & (0.1116) & (0.1113) \tabularnewline
Gender;Connected & 0.0645 & 0.0357 & 0.0304 \tabularnewline
p-value & (0.4149) & (0.652) & (0.6505) \tabularnewline
Gender;Separate & 0.2398 & 0.2283 & 0.1941 \tabularnewline
p-value & (0.0021) & (0.0035) & (0.0038) \tabularnewline
Gender;Learning & 0.1189 & 0.1077 & 0.0948 \tabularnewline
p-value & (0.1319) & (0.1724) & (0.1717) \tabularnewline
Gender;Software & 0.1634 & 0.1898 & 0.166 \tabularnewline
p-value & (0.0377) & (0.0156) & (0.016) \tabularnewline
Gender;Happiness & 0.1818 & 0.1643 & 0.1422 \tabularnewline
p-value & (0.0206) & (0.0367) & (0.0371) \tabularnewline
Gender;Depression & 0.0448 & 0.0654 & 0.0561 \tabularnewline
p-value & (0.5711) & (0.4082) & (0.4065) \tabularnewline
Gender;Belonging & 0.1434 & 0.1689 & 0.1409 \tabularnewline
p-value & (0.0687) & (0.0317) & (0.0321) \tabularnewline
Age;Connected & 0.1478 & 0.1481 & 0.1122 \tabularnewline
p-value & (0.0606) & (0.0599) & (0.0675) \tabularnewline
Age;Separate & 0.1057 & 0.1124 & 0.0898 \tabularnewline
p-value & (0.1807) & (0.1544) & (0.1433) \tabularnewline
Age;Learning & 0.0506 & 0.0098 & 0.0075 \tabularnewline
p-value & (0.5228) & (0.9018) & (0.9065) \tabularnewline
Age;Software & -0.0602 & -0.0681 & -0.0552 \tabularnewline
p-value & (0.4463) & (0.389) & (0.3822) \tabularnewline
Age;Happiness & 0.0166 & -0.0337 & -0.0235 \tabularnewline
p-value & (0.8337) & (0.6707) & (0.707) \tabularnewline
Age;Depression & 0.0309 & 0.0179 & 0.0133 \tabularnewline
p-value & (0.6964) & (0.8208) & (0.8298) \tabularnewline
Age;Belonging & -0.0678 & -0.0234 & -0.0188 \tabularnewline
p-value & (0.3913) & (0.7675) & (0.7554) \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
Connected;Depression & -0.1203 & -0.1676 & -0.128 \tabularnewline
p-value & (0.1274) & (0.033) & (0.026) \tabularnewline
Connected;Belonging & 0.0805 & 0.0983 & 0.0718 \tabularnewline
p-value & (0.3083) & (0.2131) & (0.1997) \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
Separate;Depression & -0.0783 & -0.036 & -0.0297 \tabularnewline
p-value & (0.3219) & (0.6492) & (0.606) \tabularnewline
Separate;Belonging & -0.0226 & -0.0219 & -0.0142 \tabularnewline
p-value & (0.7752) & (0.7824) & (0.7999) \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
Learning;Depression & -0.2327 & -0.2515 & -0.1892 \tabularnewline
p-value & (0.0029) & (0.0012) & (0.0015) \tabularnewline
Learning;Belonging & 0.089 & 0.1872 & 0.1468 \tabularnewline
p-value & (0.2601) & (0.017) & (0.0113) \tabularnewline
Software;Happiness & 0.074 & 0.0312 & 0.0241 \tabularnewline
p-value & (0.3492) & (0.6933) & (0.6863) \tabularnewline
Software;Depression & -0.1349 & -0.0649 & -0.0499 \tabularnewline
p-value & (0.087) & (0.4121) & (0.3988) \tabularnewline
Software;Belonging & 0.038 & 0.0543 & 0.0389 \tabularnewline
p-value & (0.6309) & (0.4925) & (0.4996) \tabularnewline
Happiness;Depression & -0.5442 & -0.4738 & -0.3724 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Happiness;Belonging & 0.2856 & 0.3618 & 0.2635 \tabularnewline
p-value & (2e-04) & (0) & (0) \tabularnewline
Depression;Belonging & -0.274 & -0.2906 & -0.2136 \tabularnewline
p-value & (4e-04) & (2e-04) & (2e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198240&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;Age[/C][C]0.0793[/C][C]0.1255[/C][C]0.1149[/C][/ROW]
[ROW][C]p-value[/C][C](0.3161)[/C][C](0.1116)[/C][C](0.1113)[/C][/ROW]
[ROW][C]Gender;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]Gender;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]Gender;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]Gender;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]Gender;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]Gender;Depression[/C][C]0.0448[/C][C]0.0654[/C][C]0.0561[/C][/ROW]
[ROW][C]p-value[/C][C](0.5711)[/C][C](0.4082)[/C][C](0.4065)[/C][/ROW]
[ROW][C]Gender;Belonging[/C][C]0.1434[/C][C]0.1689[/C][C]0.1409[/C][/ROW]
[ROW][C]p-value[/C][C](0.0687)[/C][C](0.0317)[/C][C](0.0321)[/C][/ROW]
[ROW][C]Age;Connected[/C][C]0.1478[/C][C]0.1481[/C][C]0.1122[/C][/ROW]
[ROW][C]p-value[/C][C](0.0606)[/C][C](0.0599)[/C][C](0.0675)[/C][/ROW]
[ROW][C]Age;Separate[/C][C]0.1057[/C][C]0.1124[/C][C]0.0898[/C][/ROW]
[ROW][C]p-value[/C][C](0.1807)[/C][C](0.1544)[/C][C](0.1433)[/C][/ROW]
[ROW][C]Age;Learning[/C][C]0.0506[/C][C]0.0098[/C][C]0.0075[/C][/ROW]
[ROW][C]p-value[/C][C](0.5228)[/C][C](0.9018)[/C][C](0.9065)[/C][/ROW]
[ROW][C]Age;Software[/C][C]-0.0602[/C][C]-0.0681[/C][C]-0.0552[/C][/ROW]
[ROW][C]p-value[/C][C](0.4463)[/C][C](0.389)[/C][C](0.3822)[/C][/ROW]
[ROW][C]Age;Happiness[/C][C]0.0166[/C][C]-0.0337[/C][C]-0.0235[/C][/ROW]
[ROW][C]p-value[/C][C](0.8337)[/C][C](0.6707)[/C][C](0.707)[/C][/ROW]
[ROW][C]Age;Depression[/C][C]0.0309[/C][C]0.0179[/C][C]0.0133[/C][/ROW]
[ROW][C]p-value[/C][C](0.6964)[/C][C](0.8208)[/C][C](0.8298)[/C][/ROW]
[ROW][C]Age;Belonging[/C][C]-0.0678[/C][C]-0.0234[/C][C]-0.0188[/C][/ROW]
[ROW][C]p-value[/C][C](0.3913)[/C][C](0.7675)[/C][C](0.7554)[/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]Connected;Depression[/C][C]-0.1203[/C][C]-0.1676[/C][C]-0.128[/C][/ROW]
[ROW][C]p-value[/C][C](0.1274)[/C][C](0.033)[/C][C](0.026)[/C][/ROW]
[ROW][C]Connected;Belonging[/C][C]0.0805[/C][C]0.0983[/C][C]0.0718[/C][/ROW]
[ROW][C]p-value[/C][C](0.3083)[/C][C](0.2131)[/C][C](0.1997)[/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]Separate;Depression[/C][C]-0.0783[/C][C]-0.036[/C][C]-0.0297[/C][/ROW]
[ROW][C]p-value[/C][C](0.3219)[/C][C](0.6492)[/C][C](0.606)[/C][/ROW]
[ROW][C]Separate;Belonging[/C][C]-0.0226[/C][C]-0.0219[/C][C]-0.0142[/C][/ROW]
[ROW][C]p-value[/C][C](0.7752)[/C][C](0.7824)[/C][C](0.7999)[/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]Learning;Depression[/C][C]-0.2327[/C][C]-0.2515[/C][C]-0.1892[/C][/ROW]
[ROW][C]p-value[/C][C](0.0029)[/C][C](0.0012)[/C][C](0.0015)[/C][/ROW]
[ROW][C]Learning;Belonging[/C][C]0.089[/C][C]0.1872[/C][C]0.1468[/C][/ROW]
[ROW][C]p-value[/C][C](0.2601)[/C][C](0.017)[/C][C](0.0113)[/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]
[ROW][C]Software;Depression[/C][C]-0.1349[/C][C]-0.0649[/C][C]-0.0499[/C][/ROW]
[ROW][C]p-value[/C][C](0.087)[/C][C](0.4121)[/C][C](0.3988)[/C][/ROW]
[ROW][C]Software;Belonging[/C][C]0.038[/C][C]0.0543[/C][C]0.0389[/C][/ROW]
[ROW][C]p-value[/C][C](0.6309)[/C][C](0.4925)[/C][C](0.4996)[/C][/ROW]
[ROW][C]Happiness;Depression[/C][C]-0.5442[/C][C]-0.4738[/C][C]-0.3724[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Happiness;Belonging[/C][C]0.2856[/C][C]0.3618[/C][C]0.2635[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Depression;Belonging[/C][C]-0.274[/C][C]-0.2906[/C][C]-0.2136[/C][/ROW]
[ROW][C]p-value[/C][C](4e-04)[/C][C](2e-04)[/C][C](2e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198240&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198240&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
Gender;Age	0.0793	0.1255	0.1149
p-value	(0.3161)	(0.1116)	(0.1113)
Gender;Connected	0.0645	0.0357	0.0304
p-value	(0.4149)	(0.652)	(0.6505)
Gender;Separate	0.2398	0.2283	0.1941
p-value	(0.0021)	(0.0035)	(0.0038)
Gender;Learning	0.1189	0.1077	0.0948
p-value	(0.1319)	(0.1724)	(0.1717)
Gender;Software	0.1634	0.1898	0.166
p-value	(0.0377)	(0.0156)	(0.016)
Gender;Happiness	0.1818	0.1643	0.1422
p-value	(0.0206)	(0.0367)	(0.0371)
Gender;Depression	0.0448	0.0654	0.0561
p-value	(0.5711)	(0.4082)	(0.4065)
Gender;Belonging	0.1434	0.1689	0.1409
p-value	(0.0687)	(0.0317)	(0.0321)
Age;Connected	0.1478	0.1481	0.1122
p-value	(0.0606)	(0.0599)	(0.0675)
Age;Separate	0.1057	0.1124	0.0898
p-value	(0.1807)	(0.1544)	(0.1433)
Age;Learning	0.0506	0.0098	0.0075
p-value	(0.5228)	(0.9018)	(0.9065)
Age;Software	-0.0602	-0.0681	-0.0552
p-value	(0.4463)	(0.389)	(0.3822)
Age;Happiness	0.0166	-0.0337	-0.0235
p-value	(0.8337)	(0.6707)	(0.707)
Age;Depression	0.0309	0.0179	0.0133
p-value	(0.6964)	(0.8208)	(0.8298)
Age;Belonging	-0.0678	-0.0234	-0.0188
p-value	(0.3913)	(0.7675)	(0.7554)
Connected;Separate	0.3682	0.3243	0.2413
p-value	(0)	(0)	(0)
Connected;Learning	0.2137	0.2076	0.1586
p-value	(0.0063)	(0.008)	(0.0072)
Connected;Software	0.0622	0.0748	0.0549
p-value	(0.4317)	(0.3439)	(0.3491)
Connected;Happiness	0.1427	0.1717	0.1274
p-value	(0.0701)	(0.0289)	(0.0283)
Connected;Depression	-0.1203	-0.1676	-0.128
p-value	(0.1274)	(0.033)	(0.026)
Connected;Belonging	0.0805	0.0983	0.0718
p-value	(0.3083)	(0.2131)	(0.1997)
Separate;Learning	0.0796	0.0878	0.0665
p-value	(0.3139)	(0.2666)	(0.2597)
Separate;Software	0.0679	0.1111	0.0787
p-value	(0.3906)	(0.1594)	(0.1795)
Separate;Happiness	0.1537	0.1543	0.1097
p-value	(0.0509)	(0.05)	(0.0589)
Separate;Depression	-0.0783	-0.036	-0.0297
p-value	(0.3219)	(0.6492)	(0.606)
Separate;Belonging	-0.0226	-0.0219	-0.0142
p-value	(0.7752)	(0.7824)	(0.7999)
Learning;Software	0.5456	0.4881	0.3906
p-value	(0)	(0)	(0)
Learning;Happiness	0.1829	0.1553	0.1199
p-value	(0.0198)	(0.0484)	(0.0461)
Learning;Depression	-0.2327	-0.2515	-0.1892
p-value	(0.0029)	(0.0012)	(0.0015)
Learning;Belonging	0.089	0.1872	0.1468
p-value	(0.2601)	(0.017)	(0.0113)
Software;Happiness	0.074	0.0312	0.0241
p-value	(0.3492)	(0.6933)	(0.6863)
Software;Depression	-0.1349	-0.0649	-0.0499
p-value	(0.087)	(0.4121)	(0.3988)
Software;Belonging	0.038	0.0543	0.0389
p-value	(0.6309)	(0.4925)	(0.4996)
Happiness;Depression	-0.5442	-0.4738	-0.3724
p-value	(0)	(0)	(0)
Happiness;Belonging	0.2856	0.3618	0.2635
p-value	(2e-04)	(0)	(0)
Depression;Belonging	-0.274	-0.2906	-0.2136
p-value	(4e-04)	(2e-04)	(2e-04)

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code