Question

Select the correct answer.

Answer 1

Answer:

Correct Answer (A)

We can be 95% certain that the sample mean will fall within $44.87 and $46.93

Step-by-step explanation:

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Answer 2

Answer:

We can be 95% certain that the sample mean will fall within $44.87 and $46.93

Step-by-step explanation:

Empirical Rule:

68% of the measures are within 1 standard deviation of the mean.

95% of the measures are within 2 standard deviation of the mean.

99.7% of the measures are within 3 standard deviations of the mean.

Central Limit Theorem:

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Population:

Mean $45.90, standard deviation $10.31.

Sample:

By the Central limit theorem, mean $45.90, standard deviation $s = \frac{10.31}{\sqrt{400}} = \frac{10.31}{20} = 0.5155$

Which interval can the branch manager be 95% certain that the sample mean will fall within?

By the Empirical Rule, within 2 standard deviations of the mean. So

45.90 - 2*0.5155 = $44.87

45.90 + 2*0.5155 = $46.93

We can be 95% certain that the sample mean will fall within $44.87 and $46.93