Respuesta :
Answer:
The random variable [tex]\bar x[/tex] has approximately a normal distribution because of the central limit theorem.
Step-by-step 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,
[tex]\mu_{\bar x}=\mu[/tex]
And the standard deviation of the sample means is given by,
[tex]\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}[/tex]
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 ([tex]\bar x[/tex]) will be approximately normally distributed.
