Final answer:
Without specific data on the number of friends liking mushroom and pepperoni pizza, the percentage cannot be determined. For the reference information, the appropriate distribution for a hypothesis test comparing expected and actual preference rates is the binomial distribution.
Step-by-step explanation:
The question does not provide enough information to determine the percentage of friends who like mushroom and pepperoni pizza. To calculate a percentage, specific data is required regarding the number of friends who like both of those pizza toppings compared to the total number of friends. As such, an answer cannot be deduced without additional information. In order to perform a hypothesis test in this situation, we need to determine the appropriate distribution to use. Since the test involves comparing the proportion of people who preferred Brand A with the proportion of people who preferred Brand A in the population, we can use the binomial distribution. The binomial distribution is commonly used when dealing with categorical data and comparing proportions.
To perform the hypothesis test, we would use the sample proportion of 39% as the observed proportion and the hypothesized proportion of 42% as the expected proportion. We would then calculate the p-value to determine if the difference between the observed and expected proportions is statistically significant.However, regarding the provided reference information, when considering whether to use a distribution for a hypothesis test, given that 42 percent of respondents in a taste test are expected to prefer Brand A, but in an actual test of 100 people, 39 percent preferred Brand A, the binomial distribution would typically be used. The binomial distribution is appropriate for this hypothesis test because it deals with the number of successes in a fixed number of trials, with each trial having two possible outcomes (in this case, preferring Brand A or not).