Step 1 :We are given two samples, one of adults with no children under the age of 18 and another of adults with children under the age of 18. We are asked to construct a 95% confidence interval for the difference in mean leisure time between these two groups.
Step 2 :The formula for a confidence interval for the difference between two means is: \[\bar{x}_1 - \bar{x}_2 \pm z \sqrt{\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2}}\] where \(\bar{x}_1\) and \(\bar{x}_2\) are the sample means, \(s_1\) and \(s_2\) are the sample standard deviations, \(n_1\) and \(n_2\) are the sample sizes, and \(z\) is the z-score corresponding to the desired level of confidence.
Step 3 :In this case, we have \(\bar{x}_1 = 5.33\), \(s_1 = 2.46\), \(n_1 = 40\), \(\bar{x}_2 = 4.39\), \(s_2 = 1.53\), \(n_2 = 40\), and \(z = 1.96\) for a 95% confidence level.
Step 4 :We can plug these values into the formula to calculate the confidence interval.
Step 5 :The $95 \%$ confidence interval for the difference in mean leisure time between adults with no children and adults with children is \(\boxed{(0.04, 1.84)}\) hours. This means we are $95 \%$ confident that the true difference in mean leisure time between the two groups lies within this interval. Since the interval does not contain zero, we can conclude that there is a significant difference in the number of leisure hours between adults with no children and adults with children. Therefore, the correct interpretation is option A.