The given data and their frequencies are expanded to create a complete dataset. The expanded data is:
\[
\text{Expanded Data} = [2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 6, 6, 8, 8, 8, 8, 16, 16, 16, 16, 16, 16, 17, 17, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20]
\]
The mean \( \mu \) is calculated using the formula:
\[
\mu = \frac{\sum_{i=1}^N x_i}{N}
\]
Where \( \sum_{i=1}^N x_i = 403 \) and \( N = 35 \). Thus,
\[
\mu = \frac{403}{35} = 11.51
\]
The variance \( \sigma^2 \) is calculated using the formula:
\[
\sigma^2 = \frac{\sum (x_i - \mu)^2}{n-1}
\]
Where the calculated variance is \( 54.32 \). The sample standard deviation \( \sigma \) is then:
\[
\sigma = \sqrt{54.32} = 7.37
\]
The sample standard deviation of the dataset is \( 7.37 \).