To compute the standard deviation, we first need the array of distances from the mean. So, we consider the difference between each element of the dataset and the mean:
![20-22, 12-22, 27-22, 23-22, 18-22, 20-22, 30-22, 26-22](https://img.qammunity.org/2019/formulas/mathematics/high-school/ggu02bpwv9f7ns2fvohjbasi0r0rp5s0s3.png)
which is
![-2, 10, 5, 1, -4, -2, 8, 4](https://img.qammunity.org/2019/formulas/mathematics/high-school/ade4kdckbj96d6xmprg10pfr3cnwty8tb8.png)
Then, we need to square this array:
![4, 100, 25, 1, 16, 4, 64, 16](https://img.qammunity.org/2019/formulas/mathematics/high-school/g935kwzk0mjmtkrvdnyxkxhlfvzid2a99u.png)
Then, we consider the mean of this new array, so we sum its components and divide by the number of elements:
![(4+ 100+ 25+ 1+ 16+4+ 64+ 16)/(8) = (230)/(8) = (115)/(4)](https://img.qammunity.org/2019/formulas/mathematics/high-school/dpf3c0p0gz6phce2vpaqla3kpp0azgt1u7.png)
This is the variance, i.e. the standard deviation squared. So, we only need to take the square root of the variance to get the standard deviation:
![\sigma = \sqrt{(115)/(4)} = (√(115))/(2) \approx 5.36](https://img.qammunity.org/2019/formulas/mathematics/high-school/sl6r6lo9vj2b127z7ddgb25aeeemjtwwgu.png)