Which of the following is true about the relationship between standard deviation and variance?

Standard deviation provides a measure in the same units as the data, which is why it is the correct answer. The standard deviation is calculated by taking the square root of the variance, and since variance is the average of the squared deviations from the mean, its units are the square of the units of the data. When you take the square root to find the standard deviation, you return to the original units of the data, making standard deviation particularly useful for understanding the dispersion of a dataset in a way that is directly applicable to the data itself.

In contrast, the other statements do not accurately describe the relationship between standard deviation and variance. The standard deviation is actually less than variance for any data set greater than 1 because variance is a squared measure, which leads to a larger value. Variance is not the square root of the standard deviation; rather, standard deviation is the square root of variance. Therefore, the idea that variance and standard deviation cannot be compared is incorrect, as they are indeed related and can be compared meaningfully.