Answer:
Explanation:
We would set up the hypothesis test. This is a test of a single population mean since we are dealing with mean
a) For the null hypothesis,
P = 0.21
For the alternative hypothesis,
P > 0.21
Considering the population proportion, probability of success, p = 0.21
q = probability of failure = 1 - p
q = 1 - 0.21 = 0.79
Considering the sample,
Sample proportion, p = x/n
Where
x = number of success = 100
n = number of samples = 400
p = 100/400 = 0.25 = 25%
The z statistic is calculated and the probability value is determined
The P-value describes the strength of the evidence against the null hypothesis. Therefore, the p-value is best interpreted as the following:
b. The p-value indicates the probability of observing the proportion of people who like new flavor equal to 25% or greater in the sample of 400 individuals, if actual proportion of people who like the new flavor is 21%.