A variable of a population is normally distributed with mean $\mu$and standard deviation $\sigma$. For samples of size $n$, fill in the blanks. Justify your answers.

a. Approximately $68\%$of all possible samples have means that lie within of the population mean, $\mu$

b. Approximately $95\%$of all possible samples have means that lie within of the population mean, $\mu$

c. Approximately $99.7\%$of all possible samples have means that lie within of the population mean, $\mu$

d. $100(1-\alpha )\%$of all possible samples have means that lie within $\_$of the population mean, $\mu$(Hint: Draw a graph for the distribution of $x$, and determine the $z-$scores dividing the area under the normal curve into a middle $1-\alpha$area and two outside areas of$\alpha /2$

The sampling distribution is also normally distributed with sample mean $\mu$ and standard deviation ${\sigma }_{\overline{x}}=\frac{\sigma }{\sqrt{n}}$ for a population with a mean ${\mu }_x$ and standard deviation $\sigma$

$\text{population mean and standard deviation:}{\mu }_{\overline{x}}=\mu \text{and}{\sigma }_{\overline{x}}=\sigma /\sqrt{n}\text{.}$

The empirical rule is also known as the $68-95-99.7$ rule for the normal distribution. The following is a diagrammatic depiction of the empirical rule:

As a result, roughly $68\%$ of all feasible samples have means within $\frac{\sigma }{\sqrt{n}}$ of the population mean, $\mu$

Approximately $95\%$ of all feasible samples have means that are within $\frac{2\sigma }{\sqrt{n}}$ of the population mean, $\mu$, according to empirical rule.

Approximately $99.7\%$of all feasible samples have means that are within the population mean, $\mu$ according to empirical rule.

The area under the curve on either side of the shaded zone is symmetric and represents $\frac{\alpha }{2}$, as seen in the graph.

As a result, $100(1-)\%$of all feasible samples have means that are within $z_{\frac{\alpha }{2}}\frac{\sigma }{\sqrt{n}}$of the population mean,$\mu$