Statistics Solutions

(All Steps) Sometimes correlation matrices are used to test out unusual speculations, or apparently unrelated ideas. The limitation however is causality

Question: Sometimes correlation matrices are used to test out unusual speculations, or apparently unrelated ideas. The limitation however is causality (not casualty). Dependence does not necessarily mean cause , it can be coincidental.

In the following data set, please do the following:

  1. Construct a correlation matrix around the following data set. Note the critical t-scores are dependent on the size of the array (n x m).
Population % drivers using seat belts. Avg checking Balance % Never out of county % households with 2 dogs or more
Modesto 180000 84 510 10 18
Manteca 63000 88 540 5 15
Turlock 42000 80 760 10 14
Elk Grove 137000 97 1000 2 8
Stockton 250000 90 540 7 15
Lodi 65000 90 615 8 10
Tracy 55000 95 970 3 6

Discuss all significant (defined as α ≤ 0.05) observations, and interpret the results. Pay particular attention to the correct interpretation of negative, as well as positive correlation. Are the significant observations coincidental, or are they causes?

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Solution: The downloadable solution consists of 2 pages
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