PLEASE HELP ME ANSWER THIS QUESTION ASAP!! WILL RATE!

Chronic exposure to silica dust in manufacturing environments can lead to silicosis, a chronic inflammatory disease which leads to thickening of alveoli sacs and reduced ability to breathe. Roursgaard et al (2008) studied silicosis in mice by measuring level of MIP-2 (macrophage inflammatory protein-2). He found in the lungs of a sample of 23 mice exposed to 50 ug of silica dust a mean and standard deviation of MIP-2 = 11.4 +5.75 pg/ml. The data are only slightly to moderately skewed with no outliers based on the 1.50QR criteria. Considering the central limit theorem, what can you assume regarding the sampling distribution? Since the data distribution is only modestly skewed and there are no outliers based on the 1.50QR criteria, I would need a sample size greater than 40 in order to assume a normal sampling distribution Since the data distribution is only modestly skewed and there are no outliers based on the 1.51QR criteria, and the sample size is between 15 and 30, I may assume a normal sampling distribution. Since the data distribution is only modestly skewed and there are no outliers based on the 1.51QR criteria, and the sample size is between 15 and 30, I can not assume a normal sampling distribution. I can assume the population distribution is normal, thus the sampling distribution will be normal