Step 1: Calculate the mean (\( \bar{x} \)) of the dataset.
\[
\bar{x} = \frac{\sum x_i}{n} = \frac{8 + 12 + 13 + 15 + 22}{5} = 14.
\]
Step 2: Determine the squared differences of each data point from the mean.
\[
(x_i - \bar{x})^2 = \{(8-14)^2, (12-14)^2, (13-14)^2, (15-14)^2, (22-14)^2\}.
\]
\[
(x_i - \bar{x})^2 = \{36, 4, 1, 1, 64\}.
\]
Step 3: Compute the variance.
\[
\text{Variance (Var(x))} = \frac{\sum (x_i - \bar{x})^2}{n} = \frac{36 + 4 + 1 + 1 + 64}{5} = \frac{106}{5} = 21.2.
\]
Final Answer:
The variance for the provided data is:
\[
\boxed{21.2}
\]