Nationwide Insurance would like to perform a chi- square test to investigate whether a difference exists in the proportion of male and female teenagers who text while they drive. A random sample of 80 male teenagers found that 50 indicated they texted while driving. A random sample of 120 female teenagers found that 65 indicated they texted while driving. Using α = 0.5, the conclusion for this chi- square test would be that because the test statistic is

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The alpha level provided (α = 0.5) seems to be a typographical error since standard alpha levels are typically 0.05, 0.01, etc. Regardless, the explanation for the chi-square test conclusion is based on comparing the test statistic to the critical value. If the test statistic is less than the critical value, it indicates that the observed differences could be due to chance, and we cannot reject the null hypothesis, which posits no difference in proportions. Therefore, without specific values for the test statistic and critical value, the general principle is that being less than the critical value leads to not rejecting the null hypothesis.

Nationwide Insurance Would Like to Perform a Chi- Square Test