What conculsion can you draw from this correlation coefficie

What conculsion can you draw from this correlation coefficients matrix?

Correlation Coefficients Matrix

Missing values removal	Pairwise deletion



		80	80	50	60	60	70	70	50

80	R	1

	R Standard Error

	t

	p-value

	H0 (1%)

80	R	0.42445	1

	R Standard Error	0.05466

	t	1.81552

	p-value	0.08949

	H0 (1%)	accepted

50	R	0.59138	0.51673	1

	R Standard Error	0.04335	0.04887

	t	2.84029	2.33752

	p-value	0.01241	0.03368

	H0 (1%)	accepted	accepted

60	R	0.26517	0.7036	0.54558	1

	R Standard Error	0.06198	0.03366	0.04682

	t	1.06511	3.83482	2.52131

	p-value	0.30367	0.00162	0.0235

	H0 (1%)	accepted	rejected	accepted

60	R	0.29647	0.15538	0.49004	0.38021	1

	R Standard Error	0.06081	0.06506	0.05066	0.05703

	t	1.20227	0.60917	2.17725	1.59211

	p-value	0.24789	0.55152	0.04584	0.13221

	H0 (1%)	accepted	accepted	accepted	accepted

70	R	0.49017	0.39983	0.31016	0.19969	0.16736	1

	R Standard Error	0.05065	0.05601	0.06025	0.06401	0.0648

	t	2.17805	1.68944	1.26355	0.7893	0.65745

	p-value	0.04577	0.11181	0.22568	0.44224	0.52085

	H0 (1%)	accepted	accepted	accepted	accepted	accepted

70	R	0.5836	0.51916	0.44542	0.31215	0.20222	0.67486	1

	R Standard Error	0.04396	0.0487	0.05344	0.06017	0.06394	0.0363

	t	2.78345	2.35258	1.92681	1.27252	0.79971	3.54192

	p-value	0.01392	0.03271	0.07316	0.22256	0.43636	0.00296

	H0 (1%)	accepted	accepted	accepted	accepted	accepted	rejected

50	R	0.27266	0.56343	0.76205	0.45955	0.42962	0.37611	0.31717	1

	R Standard Error	0.06171	0.0455	0.02795	0.05259	0.05436	0.05724	0.05996

	t	1.0976	2.64131	4.55806	2.00398	1.84263	1.57212	1.29527

	p-value	0.28969	0.01851	0.00038	0.06347	0.08524	0.13677	0.21481

	H0 (1%)	accepted	accepted	rejected	accepted	accepted	accepted	accepted



R

Variable vs. Variable	R	No# of valid cases

50 vs. 50	0.76205	17

60 vs. 80	0.7036	17

70 vs. 70	0.67486	17

50 vs. 80	0.59138	17

70 vs. 80	0.5836	17

50 vs. 80	0.56343	17

60 vs. 50	0.54558	17

70 vs. 80	0.51916	17

50 vs. 80	0.51673	17

70 vs. 80	0.49017	17

60 vs. 50	0.49004	17

50 vs. 60	0.45955	17

70 vs. 50	0.44542	17

50 vs. 60	0.42962	17

80 vs. 80	0.42445	17

70 vs. 80	0.39983	17

60 vs. 60	0.38021	17

50 vs. 70	0.37611	17

50 vs. 70	0.31717	17

70 vs. 60	0.31215	17

70 vs. 50	0.31016	17

60 vs. 80	0.29647	17

50 vs. 80	0.27266	17

60 vs. 80	0.26517	17

70 vs. 60	0.20222	17

70 vs. 60	0.19969	17

70 vs. 60	0.16736	17

60 vs. 80	0.15538	17

from the correlation matrix we can conclude that the variables

1) 50 and 50 are related by 76.205%

2) 60 and 80 are related by 70.36%

3) 70 and 70 are related by 67.486%

4) 50 and 80 are related by 59.138%

5) 70 and 80 are related by 58.36%

6) 50 and 80 are related by 56.343%

7) 60 and 50 are related by 54.556%

8) 70 and 80 are related by 51.916%

9) 50 and 80 are related by 51.673%

10) 70 and 80 are related by 49.017%

11) 60 and 50 are related by 49.004%

12) 50 and 60 are related by 45.955%

13) 70 and 50 are related by 44.542%

14) 50 and 60 are related by 42.962%

15) 80 and 80 are related by 42.445%

16) 70 and 80 are related by 39.983%

17) 60 and 60 are related by 38.021%

18) 50 and 70 are related by 37.611%

19) 50 and 70 are related by 31.717%

20) 70 and 60 are related by 31.215%

21) 70 and 50 are related by 31.016%

22) 60 and 80 are related by 29.647%

23) 50 and 80 are related by 27.266%

24) 60 and 80 are related by 26.517%

25) 70 and 60 are related by 20.222%

26) 70 and 60 are related by 19.969%

27) 70 and 60 are related by 16.736%

28) 60 and 80 are related by 15.538%

What conculsion can you draw from this correlation coefficients matrix? Correlation Coefficients Matrix Missing values removal Pairwise deletion 80 80 50 60 60

What conculsion can you draw from this correlation coefficie

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