In one region. the Sep. energy consumption levels for a single-family are to be normally distributed with a mean of 1,050 kWh and standard deviation of 218 kWh. If 50 different homes are randomly selected, find probability that their mean energy consumption is greater than 1,075 kWh.
The problem asks about the probability of the (sample) mean, so you have that the sample mean \(\bar{X}\) is normally distributed with mean the same as the population mean \(\mu =1050\) and with standard deviation being \(\dfrac{\sigma}{\sqrt{n}}\). So, when you find the z-score, you need to do the following: \[ Z=\frac{\bar{X}-\mu}{\sigma/\sqrt{n}}\] So the question asks to find \(P(\bar{X}> 1075)\) , and so by standardizing you get: \[P\left( \frac{\bar{X}-1050}{218/\sqrt{50}}>\frac{1075-1050}{218/\sqrt{50}}\right) =P(Z>0.811)\] and then use a standard normal table to fnd that probability, or a calculator/software.
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