The standard deviation \( \sigma \) of a data set is given by the formula:
\[
\sigma = \sqrt{\frac{1}{n} \sum_{i=1}^{n} (x_i - \bar{x})^2}
\]
Where:
- \( x_i \) are the data points,
- \( \bar{x} \) is the mean of the data,
- \( n \) is the number of data points.
First, find the mean \( \bar{x} \):
\[
\bar{x} = \frac{162 + 163 + 160 + 164 + 160 + 170 + 161 + 164}{8} = \frac{1344}{8} = 168
\]
Next, calculate the squared differences from the mean and sum them:
\[
(162 - 168)^2 = 36, \quad (163 - 168)^2 = 25, \quad (160 - 168)^2 = 64, \quad (164 - 168)^2 = 16, \quad (160 - 168)^2 = 64,\]
\[\quad (170 - 168)^2 = 4, \quad (161 - 168)^2 = 49, \quad (164 - 168)^2 = 16
\]
Sum of squared differences:
\[
36 + 25 + 64 + 16 + 64 + 4 + 49 + 16 = 274
\]
Now, calculate the standard deviation:
\[
\sigma = \sqrt{\frac{274}{8}} \approx 3.04
\]
Thus, the correct answer is \( 3.04 \).