We have the electricity bill as a normal random variable with mean $200 and standard deviation $33.
A sample of 36 bills is collected.
The distribution for the sample mean will have the following parameters:
[tex]\begin{gathered} \mu_s=\mu=200 \\ \sigma_s=\frac{\sigma}{\sqrt{n}}=\frac{33}{\sqrt{36}}=\frac{33}{6}=5.5 \end{gathered}[/tex]We have to calculate the probability that the sample mean is less than $194.
We will calculate the z-score for X = 194 using the sampling distribution parameters:
[tex]z=\frac{X-\mu_s}{\sigma_s}=\frac{194-200}{5.5}=\frac{-6}{5.5}\approx-1.09091[/tex]We can then use the standard normal distribution table to calculate the probability:
[tex]P(X<194)=P(z<-1.09091)\approx0.1377[/tex]We now have to find the 95th percentile for the sample mean.
This means a value for which 95% of the sample means are below this value.
We can express this as:
[tex]P(XThe z-score for a 95th percentile is z = 1.64485.We can then use the parameters of the sampling distribution to calculate the value of X as:
[tex]\begin{gathered} X_{95}=\mu_s+z_{95}\cdot\sigma_s \\ X_{95}=200+1.64485\cdot5.5\approx200+9=209 \end{gathered}[/tex]Answer:
1) P(X < 194) = 0.1377.
2) X = 209