To calculate the standard deviation, follow these steps:

Step 1: Find the mean (average)

$\text{Mean} = \frac{\text{Sum of all numbers}}{\text{Total count of numbers}} = \frac{21 + 18 + 21 + 25 + 27 + 23}{6} = \frac{135}{6} = 22.5$

Step 2: Find the squared differences from the mean

For each number, subtract the mean and square the result:

$(21 - 22.5)^2 = (-1.5)^2 = 2.25$ $(18 - 22.5)^2 = (-4.5)^2 = 20.25$ $(21 - 22.5)^2 = (-1.5)^2 = 2.25$ $(25 - 22.5)^2 = (2.5)^2 = 6.25$ $(27 - 22.5)^2 = (4.5)^2 = 20.25$ $(23 - 22.5)^2 = (0.5)^2 = 0.25$

Step 3: Find the average of these squared differences (variance)

$\text{Variance} = \frac{2.25 + 20.25 + 2.25 + 6.25 + 20.25 + 0.25}{6} = \frac{51.5}{6} \approx 8.58$

Step 4: Take the square root of the variance (standard deviation)

$\text{Standard deviation} = \sqrt{8.58} \approx 2.93$

So, the standard deviation of the numbers is approximately 2.93.

Would you like more details or have any questions?

Here are 5 related questions:

1. How does the standard deviation differ from variance?
2. What is the significance of a high or low standard deviation?
3. How does standard deviation relate to data dispersion?
4. What are some applications of standard deviation in real-world scenarios?
5. How would the result change if an outlier was added to the dataset?

Tip: The standard deviation is sensitive to outliers, so large deviations from the mean can significantly affect its value.