1. The problem involves interpreting the confidence interval for the difference in means between two regions, Northern (N) and Southern (S). 2. Given data: - Sample size for each region: $n = 31$ - Mean for Northern: $\bar{x}_N = 119.1$ - Mean for Southern: $\bar{x}_S = 119.7$ - Difference in means: $d = \bar{x}_N - \bar{x}_S = -0.6$ - Standard deviation of differences: $s_d = 1.1$ - Confidence interval for difference: $(-0.9355, -0.2645)$ 3. The confidence interval formula for the difference in means when samples are paired or differences are considered is: $$\bar{d} \pm t^* \frac{s_d}{\sqrt{n}}$$ where $\bar{d}$ is the sample mean difference, $s_d$ is the standard deviation of differences, $n$ is the sample size, and $t^*$ is the critical t-value for the desired confidence level. 4. The interval $(-0.9355, -0.2645)$ means we are confident that the true mean difference $\mu_d$ lies between these two values. 5. Since the entire interval is negative, it suggests that the Northern region's mean is significantly less than the Southern region's mean at the confidence level used. 6. The value $-0.9355$ is the lower bound and $-0.2645$ is the upper bound of the confidence interval. 7. This interval does not include zero, so the difference is statistically significant. Final answer: The confidence interval $(-0.9355, -0.2645)$ indicates a significant difference in means, with the Northern region having a lower average than the Southern region.