In probability theory and statistics, variance is used to describe the amount of variation in a population or sample of observations. The square root of Variance is useful in measuring the central tendency and dispersion of a sample or population. The definition of variance is either the expected or average value of squared deviations from the mean. (Sum of squares)/(# of observations) = Variance. Square root of Variance = Standard deviation. For the most part, standard deviation and variance are interchangeable in terms of their use and functionality due to their simple conversion of each other, however many researchers prefer standard deviation because its units are the same as those for the variable of interest.
Essentially, the standard deviation is much more useful then variance in terms of describing data, however variance is still very important for formulation purposes since it’s calculation and use is an intermediate step to calculating the standard deviation.