What conculsion can you draw from this correlation coefficients matrix? Correlat

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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

Explanation / Answer

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%

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