Based on historical data, your manager believes that 39% of the company's orders come from first-time customers. A random sample of 171 orders will be used to estimate the proportion of first-time-customers. What is the probability that the sample proportion is between 0.21 and 0.32

Respuesta :

Answer:

[tex] z= \frac{0.21- 0.39}{0.0373}= -4.829[/tex]

[tex] z= \frac{0.32- 0.39}{0.0373}=-1.877[/tex]

And we can find the probability with this difference:

[tex] P(-4.829<z< -1.877) = P(Z<-1.877) -P(Z<-4.829)=0.0303- 6.86x10^{-7}=0.0303[/tex]

Step-by-step explanation:

For this case we have the following info given:

[tex] n = 171[/tex] represent the sample size

[tex]p =0.39[/tex] the proportion of interest

We want to find the following probability:

[tex] P( 0.21 < \hat p < 0.32)[/tex]

We can use the normal approximation for this case since np >10 and n (1-p) >10

For this case we know that the distribution for the sample proportion is given by:

[tex]\hat p \sim N( p , \sqrt{\frac{p (1-p)}{n}} )[/tex]

And we can use the following parameters:

[tex] \mu_{\hat p}= 0.39[/tex]

[tex] \sigma_{\hat p} =\sqrt{\frac{0.39*(1-0.39)}{171}}= 0.0373[/tex]

And we can apply the z score formula given by:

[tex] z = \frac{p \\mu_{\hat p}}{\sigma_{\hat p}}[/tex]

And using this formula we got:

[tex] z= \frac{0.21- 0.39}{0.0373}= -4.829[/tex]

[tex] z= \frac{0.32- 0.39}{0.0373}=-1.877[/tex]

And we can find the probability with this difference:

[tex] P(-4.829<z< -1.877) = P(Z<-1.877) -P(Z<-4.829)=0.0303- 6.86x10^{-7}=0.0303[/tex]