Question

A skin care company has data on the monthly rainfall and the sales of sun screen...

A skin care company has data on the monthly rainfall and the sales of sun screen lotion for the 3 months of June, July, and August for the last 20 years. It has calculated the correlation for the 60 pairs of values. The correlation, r, is –0.310

1. The critical value for testing correlation for this data at a significance level of 0.05 (rounded to 3 decimal places) is:

2. What is the appropriate conclusion for a hypothesis test at a significance level of 0.05 on the correlation of this data, r, using the absolute value of r and the critical value?

A: absolute r < critical value, so the correlation is statistically significant

B: absolute r < critical value, so the correlation is not statistically significant

C: absolute r > critical value, so the correlation is statistically significant

D: absolute r > critical value, so the correlation is not statistically significant

E: absolute r > critical value, proving a direct causal relationship between the variables

3.When doing a hypothesis test on the correlation between two variables X and Y, which one of the following is the best explanation of the meaning of statistically significant?

A: Statistically significant means that X causes Y

B: Statistically significant means that Y causes X

C: Statistically significant means that small changes in X correspond to large changes in Y

D: Statistically significant means that there are no lurking variables

E: Statistically significant means that there is strong evidence that the correlation in the data is not due to chance.

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