In statistics, sx and σx represent different types of standard deviations:
σx (sigma) represents the population standard deviation. It is a measure of the dispersion of all data points in an entire population. It is calculated using the actual values for every member of the population.
sx represents the sample standard deviation. It is a measure of the dispersion within a sample (a subset of the population). Since it is based on a sample, the calculation includes a correction factor (dividing by n-1 instead of n, where n is the sample size) to account for the fact that a sample tends to underestimate variability.
In summary:
Use σx when working with the entire population.
Use sx when working with a sample.