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The standard deviation formula may look confusing, but it will make sense after we break it down. In the coming sections, we'll walk through a step-by-step interactive example.

The formula we use for standard deviation depends on whether the data is being considered a population of its own, or the data is a sample representing a larger population.

Thus the sample standard error (standard deviation of the sample divided by the square root of n) is the statistic we are going to be using for calculating confidence intervals, and presumably …

The standard deviation formula may look confusing, but it will make sense after we break it down. In the coming sections, we'll walk through a step-by-step interactive example.

Range, variance, and standard deviation all measure the spread or variability of a data set in different ways. The range is easy to calculate—it's the difference between the largest and …

Learn step-by-step how to calculate standard deviation on Khan Academy.

The standard deviation (sigma) is a measure of how much the data is spread out around the mean, not a better guess as to what the mean should be. A small value of sigma indicates that …

The standard deviation of a binomial distribution (σ) is derived from its variance formula (σ^2 = np (1 − p)), where n is the number of trials, and p is the probability of success. The square root is …

In population standard deviation is calculated using every individual from that population while in sample standard deviation we take specific number of individuals from the population.