Respuesta :
Answer:
By the Central Limit Theorem, the distribution of ¯ x is approximately normal with mean 187 and standard deviation 2.05.
Step-by-step explanation:
Central Limit Theorem
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
The lengths of adult males' hands are normally distributed with mean 187 mm and standard deviation is 7.1 mm.
This means that [tex]\mu = 187, \sigma = 7.1[/tex]
Suppose that 12 individuals are randomly chosen.
This means that [tex]n = 12, s = \frac{7.1}{\sqrt{12}} = 2.05[/tex]
What is the distribution of ¯ x?
By the Central Limit Theorem, the distribution of ¯ x is approximately normal with mean 187 and standard deviation 2.05.
