A potate chip manufacturer advertises that its product is packaged in 8 ounce bags. The standard deviation of the bag weight is known to be 0.5 ounces. A quality control specialist regularly checks whether the mean bag weight is less than 8 ounces. On one production run, she took a random sample of n=40 bags of potato chips and weighted them. The sample mean weight was 7.9 ounces. The quality control specialist decided to run a significance test to evaluate the claim that the bags weight 8 ounces on average. The p-value for the test is 0.10. How ould you interpret this probability? Select all that apply
A. There is a 10% probability that the population mean bag weight is 8 ounces.
B. If the population mean bag weight was 8 ounces, then there is 10% probability of obtaining a sample of 40 bags of chips with a sample mean bag weight of 7.9 ounces or smaller.
C. If the population mean bag weight was 8 ounces, then there is 10% probability of obtaining a sample of 40 bags of chips with a sample mean bag weight of 7.9 ounces or larger.
D. Non of the above is a correct interpretation of the p-value of 10%
B. If the population mean bag weight was 8 ounces, then there is 10% probability of obtaining a sample of 40 bags of chips with a sample mean bag weight of 7.9 ounces or smaller.
C. If the population mean bag weight was 8 ounces, then there is 10% probability of obtaining a sample of 40 bags of chips with a sample mean bag weight of 7.9 ounces or larger.
Both of these interpretations correctly reflect the meaning of the p-value in this context.