Flight delays impose a very large cost on the US economy. In order to better understand this phenomenon, data on flight delays was collected at 6 airports categorized as \"small,\" and 4 airports categorized as "target in the year ll. The table below displays the delays [in minutes] for the ir' small airports {with a mean of 9.3 and a standard deviation of I141] and 4 large airports [with a mean of 121] and a standard deviation of 31]}. mm-moalam \"mam-I- a. Previous research shows that delays can be assumed to have a nom'ial distribution. Find the test statistic for a null hypodie-sis that states that the population mean for the delays at the "small" category of airports in 2016 was equal to 9.5. What conclusion can you draw based on this test statistic? Can we conclude that the population variance for delays at large airports is greater than the population variance for delays at small airports, again assuming that delays come from a normal distribution? State your null hypothesis and alternate hypothesis, value of the test statistic, p- value, and conclusion. Repeat part a if previous research shows that delays cannot be assumed to have a normal distribution but have a symmetric and continuous distribution. Compute a test statistic and state what conclusions we can thaw based on this statistic. Suppose we instead know from previous research that population distributions of delays at small and large airpolts have close to identical shapes and spreads, but are not approximately normal. Compute a test statistic for the null hypothesis that population means at small and large airports are equal, and state what conclusions we can draw based on this statistic