Question

The head of maintenance at XYZ Rent-A-Car believes that the mean number of miles between services is 4959 miles, with a standard deviation of 448 miles. If he is correct, what is the probability that the mean of a sample of 43 cars would differ from the population mean by less than 111 miles

Answer 1

0.8948 = 89.48% probability that the mean of a sample of 43 cars would differ from the population mean by less than 111 miles

Explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean
`\mu` and standard deviation
`\sigma`, the z-score of a measure X is given by:

`Z = (X - \mu)/(\sigma)`

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes 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 = (\sigma)/(√(n))`.

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

The mean number of miles between services is 4959 miles, with a standard deviation of 448 miles

This means that
`\mu = 4959, \sigma = 448`

Sample of 43:

This means that
`n = 43, s = (448)/(√(43))`

What is the probability that the mean of a sample of 43 cars would differ from the population mean by less than 111 miles?

p-value of Z when X = 4959 + 111 = 5070 subtracted by the p-value of Z when X = 4959 - 111 = 4848, that is, probability the sample mean is between these two values.

X = 5070

`Z = (X - \mu)/(\sigma)`

By the Central Limit Theorem

`Z = (X - \mu)/(s)`

`Z = (5070 - 4959)/((448)/(√(43)))`

`Z = 1.62`

`Z = 1.62` has a p-value of 0.9474

X = 4848

`Z = (X - \mu)/(s)`

`Z = (4848 - 4959)/((448)/(√(43)))`

`Z = -1.62`

`Z = -1.62` has a p-value of 0.0526

0.9474 - 0.0526 = 0.8948

0.8948 = 89.48% probability that the mean of a sample of 43 cars would differ from the population mean by less than 111 miles