The sample variance is the square of the standard deviation. So, if the standard deviation of a sample is 2, the sample variance can be calculated as follows:

$\text{Sample Variance} = (\text{Standard Deviation})^2 = 2^2 = 4$

Thus, the sample variance is 4.

Would you like further details on this concept or have any other questions?

Here are five related questions to consider:

1. What is the difference between sample variance and population variance?
2. How is the standard deviation affected by adding a constant to all data points?
3. How do you calculate the sample variance from raw data?
4. What role does variance play in the analysis of data distributions?
5. How does the sample size affect the variance?

Tip: Variance measures the spread of data points around the mean, and it is always non-negative because it involves squaring the deviations.