Answer:
The probability that the sample proportion will differ from the population proportion by greater than 0.03 is 0.0143.
Step-by-step explanation:
According to the Central limit theorem, if from an unknown population large samples of sizes <em>n</em> ≥ 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.
The mean of this sampling distribution of sample proportion is:

The standard deviation of this sampling distribution of sample proportion is:

The sample selected consists of <em>n</em> = 254 individuals. The sample is quite large, i.e. <em>n</em> = 254 > 30. So the central limit theorem can be applied to approximate the distribution of sample proportion of people in the city that will purchase the products of Goofy's fast food.
The mean is:

And the standard deviation is:

Now, we need to compute the probability that the sample proportion will differ from the population proportion by greater than 0.03.
That is:

Compute the value of
as follows:


*Use a <em>z</em>-tale for the probability.
Thus, the probability that the sample proportion will differ from the population proportion by greater than 0.03 is 0.0143.
A.
1.84
will be the answer
Answer:
15x-9x=6x
please mark me as brainliest
Answer: normally distributed and will have a mean that will be approximately equal to the population mean.
Step-by-step explanation: The central limit theorem tries to show that regardless to the variables in a statistical distribution,the sample mean will tend toward approximating the mean of the population for sufficiently large sample size, a sample size or observations that are greater than or equal to 30 is sufficiently large enough.
The theorem helps to understand that as the sample size increases the chances of getting a sample mean that is approximately Equal to the population mean will be high, and the variance will continue to reduce.