In: Statistics and Probability
(a) Suppose n = 6 and the sample correlation coefficient is r = 0.882. Is r significant at the 1% level of significance (based on a two-tailed test)? (Round your answers to three decimal places.)
t | = | |
critical t | = |
Conclusion:
Yes, the correlation coefficient ρ is significantly different from 0 at the 0.01 level of significance.
No, the correlation coefficient ρ is not significantly different from 0 at the 0.01 level of significance.
(b) Suppose n = 10 and the sample correlation coefficient
is r = 0.882. Is r significant at the 1% level of
significance (based on a two-tailed test)? (Round your answers to
three decimal places.)
t | = | |
critical t | = |
Conclusion:
Yes, the correlation coefficient ρ is significantly different from 0 at the 0.01 level of significance.
No, the correlation coefficient ρ is not significantly different from 0 at the 0.01 level of significance.
(c) Explain why the test results of parts (a) and (b) are different
even though the sample correlation coefficient r = 0.882
is the same in both parts. Does it appear that sample size plays an
important role in determining the significance of a correlation
coefficient? Explain.
As n increases, the degrees of freedom and the test statistic decrease. This produces a smaller P value.
As n increases, so do the degrees of freedom, and the test statistic. This produces a smaller P value.
As n increases, so do the degrees of freedom, and the test statistic. This produces a larger P value.
As n decreases, the degrees of freedom and the test statistic increase. This produces a smaller P value.