Answer:
The probability that the sample proportion differ from the population proportion by greater than 3% is 0.0241.
Step-by-step explanation:
Let <em>X</em> = number of phone calls that are wrong numbers.
The proportion of phone calls that are wrong numbers is, <em>p</em> = 0.08.
A sample of<em> </em><em>n</em> = 421 phone calls is selected to determine the proportion of wrong numbers in this sample.
The random variable <em>X</em> follows a Binomial distribution with parameters <em>n</em> and <em>p</em>.
The probability mass function of a Binomial distribution is:
Now, for the sample proportion to differ from the population proportion by 3% the value of the sample proportion should be:
So when the sample proportion is less than 5% or greater than 11% the difference between the sample proportion and population proportion will be greater than 3%.
- If sample proportion is 5% then the value of <em>X</em> is,
Compute the value of P (X ≤ 21) as follows:
- If the sample proportion is 11% then the value of <em>X</em> is,
Compute the value of P (X ≥ 47) as follows:
Then the probability that the sample proportion differ from the population proportion by greater than 3% is:
Thus, the probability that the sample proportion differ from the population proportion by greater than 3% is 0.0241.