Final answer:
To compute the variance, one must square the standard deviation (B). Variance is calculated differently depending on whether the data is from a sample or an entire population, but in both cases, it is derived from squaring the standard deviation.
Step-by-step explanation:
To compute the variance, one should square the standard deviation. Variance is defined as the mean of the squared deviations from the mean for a set of data. In formula terms, for a sample variance (s²), you would take the sum of the squares of the deviations and divide by n - 1, where n is the sample size. This is because the sample variance (s²) is an estimate of the population variance, and dividing by (n - 1) gives a more accurate estimate. Therefore, the correct answer for computing the variance would be to square the standard deviation (Option B).
To compute the variance, one should square the standard deviation.
The variance is the average of the squares of the deviations. It is a squared measure and does not have the same units as the data. Taking the square root of the variance gives us the standard deviation, which measures the spread in the same units as the data.