Respuesta :
Answer:
A) The sampling distribution for a sample size n=50 has a mean of 18.5 weeks and a standard deviation of 0.849.
B) P = 0.7616
C) P = 0.4441
Step-by-step explanation:
We assume that for the population of all unemployed individuals the population mean length of unemployment is 18.5 weeks and that the population standard deviation is 6 weeks.
A) We take a sample of size n=50.
The mean of the sampling distribution is equal to the population mean:
[tex]\mu_s=\mu=18.5[/tex]
The standard deviation of the sampling distribution is:
[tex]\sigma_s=\dfrac{\sigma}{\sqrt{n}}=\dfrac{6}{\sqrt{50}}=0.849[/tex]
B) We have to calculate the probability that the sampling distribution gives a value between one week from the mean. That is between 17.5 and 19.5 weeks.
We can calculate this with the z-scores:
[tex]z_1=\dfrac{X_1-\mu}{\sigma/\sqrt{n}}=\dfrac{17.5-18.5}{6/\sqrt{50}}=\dfrac{-1}{0.8485}=-1.179\\\\\\z_2=\dfrac{X_2-\mu}{\sigma/\sqrt{n}}=\dfrac{19.5-18.5}{6/\sqrt{50}}=\dfrac{1}{0.8485}=1.179[/tex]
The probability it then:
[tex]P(|X_s-\mu_s|<1)=P(|z|<1.179)=0.7616[/tex]
C) For half a week (between 18 and 19 weeks), we recalculate the z-scores and the probabilities:
[tex]z=\dfrac{X-\mu}{\sigma/\sqrt{n}}=\dfrac{18-18.5}{6/\sqrt{50}}=\dfrac{-0.5}{0.8485}=-0.589[/tex]
[tex]P(|X_s-\mu_s|<0.5)=P(|z|<0.589)=0.4441[/tex]