Answer:
The random variable
has approximately a normal distribution because of the central limit theorem.
Explanation:
According to the Central Limit Theorem if we have an unknown population with mean μ and standard deviation σ and appropriately huge random samples (n ≥ 30) are selected from the population with replacement, then the sampling distribution of the sample mean will be approximately normally distributed.
Then, the mean of the sample means is given by,
And the standard deviation of the sample means is given by,
![\sigma_(\bar x)=(\sigma)/(√(n))](https://img.qammunity.org/2021/formulas/mathematics/college/fc0t4wrqsc650sm3kempki0q4p4n5sf588.png)
Let the random variable X be defined as the age of cars owned by residents of a small city.
It is provided that:
μ = 6 years
σ = 2.2 years
n = 400
As the sample selected is too large, i.e. n = 400 > 30, according to the central limit theorem the sampling distribution of the sample mean (
) will be approximately normally distributed.