The weekly salaries of a sample of employees at the local bank are given in the table below.

\begin{tabular}{|c|c|}
\hline
Employee & Weekly Salary \\
\hline
Anja & [tex]$\$[/tex]245[tex]$ \\
\hline
Raz & $[/tex]\[tex]$300$[/tex] \\
\hline
Natalie & [tex]$\$[/tex]325[tex]$ \\
\hline
Mic & $[/tex]\[tex]$465$[/tex] \\
\hline
Paul & [tex]$\$[/tex]100$ \\
\hline
\end{tabular}

What is the variance for the data?

Variance:
[tex]\[
\frac{\left(x_1 - \bar{x}\right)^2 + \left(x_2 - \bar{x}\right)^2 + \ldots + \left(x_n - \bar{x}\right)^2}{n - 1}
\][/tex]

A. 118.35
B. 13232



Answer :

To find the variance of the weekly salaries of the employees at the local bank, we need to follow these steps:

1. Calculate the Mean (Average) Salary:
The mean salary is the sum of all salaries divided by the number of employees.

[tex]\( \text{Mean Salary (\(\bar{x}\)[/tex])} = \frac{\[tex]$245 + \$[/tex]300 + \[tex]$325 + \$[/tex]465 + \[tex]$100}{5} = \$[/tex]287.0 \)

2. Calculate the Squared Differences from the Mean:
For each salary, subtract the mean salary and then square the result:

- For Anja: [tex]\((245 - 287)^2 = (-42)^2 = 1764.0\)[/tex]
- For Raz: [tex]\((300 - 287)^2 = (13)^2 = 169.0\)[/tex]
- For Natalie: [tex]\((325 - 287)^2 = (38)^2 = 1444.0\)[/tex]
- For Mic: [tex]\((465 - 287)^2 = (178)^2 = 31684.0\)[/tex]
- For Paul: [tex]\((100 - 287)^2 = (-187)^2 = 34969.0\)[/tex]

So the squared differences are [tex]\([1764.0, 169.0, 1444.0, 31684.0, 34969.0]\)[/tex].

3. Sum of Squared Differences:
Add up all the squared differences:

[tex]\( 1764.0 + 169.0 + 1444.0 + 31684.0 + 34969.0 = 70030.0 \)[/tex]

4. Calculate the Variance:
Finally, divide the sum of squared differences by the number of salaries minus one (n-1), where [tex]\( n \)[/tex] is the number of employees.

[tex]\( \text{Variance} = \frac{70030.0}{5 - 1} = \frac{70030.0}{4} = 17507.5 \)[/tex]

The variance for the weekly salaries of the employees is [tex]\( 17507.5 \)[/tex].