Suppose the Age Distribution of the Canadian Population and the Age

Multiple Choice

Suppose the age distribution of the Canadian population and the age distribution of a random sample of 492 residents in the Indian community of Red Lake are shown below. $$\begin{array} { l l l } & & \text { Observed Number } \\\text { Age (years) } & \text { Percent of Canadian Population } & \text { in Red Lake Village } \\\hline \text { Under } 5 & 8.5 \% & 33 \\5 \text { to } 14 & 10.3 \% & 38 \\15 \text { to } 64 & 70.5 \% & 373 \\65 \text { and older } & 10.7 \% & 48 \\\hline\end{array}$$ Use to test the claim that the age distribution of the general Canadian population fits the age distribution of the residents of Red Lake Village. Given that 0.05 < P-Value < 0.10, will you reject or fail to reject the null hypothesis that the population fits the specified distribution of categories?
$$\alpha = 0.01$$

A) Since the P-Value is less than $\alpha$ , we fail to reject the null hypothesis that the variables are independent. At 0.01 level of significance, we conclude that the variables are not independent.
B) Since the P-Value is less than $\alpha$ , we reject the null hypothesis that the variables are independent. At 0.01 level of significance, we conclude that the variables are not independent.
C) Since the P-Value is less than $\alpha$ , we fail to reject the null hypothesis that the variables are not independent. At 0.01 level of significance, we conclude that the variables are independent.
D) Since the P-Value is less than $\alpha$ , we reject the null hypothesis that the variables are not independent. At 0.01 level of significance, we conclude that the variables are independent.
E) Since the P-Value is greater than $\alpha$ , we fail to reject the null hypothesis that the variables are independent. At 0.01 level of significance, we conclude that the variables are not independent.