A food truck operator has traditionally sold 75 bowls of noodle soup each day. He moves to a new location and after a week sees
that he has averaged 85 bowls of noodle soup sales each day. He runs a one-sided hypothesis test to determine if his daily sales at the new location have increased. The p-value of the test is 0.031. How should he interpret the p-value? a. There is a 3.1% chance that the true mean of soup sales at the new location is 85 bowls a day.
b. There is a 96.9% chance that the true mean of soup sales at the new location is greater than 75 bowls a day.
c. There is a 96.9% chance that the sample mean of soup sales at the new location is 85 bowls a day.
d. There is a 3.1% chance of obtaining a sample with a mean of 85 or higher assuming that the true mean sales at the new location is still equal to or less than 75 bowls a day.
e. There is a 96.9% chance that the true mean of soup sales at the new location is within 3.1 bowls of 85 bowls a day.
The p-value of the test is 0.031. How should he interpret the p-value as "There is a 96.9% chance that the true mean of soup sales at the new location is greater than 75 bowls a day"
Step-by-step explanation:
P-value"In statistical hypothesis testing, the p-value or probability value is the probability of obtaining test results at least as extreme as the results actually observed during the test, assuming that the null hypothesis is correct"
