Variance measures how much each score in a data set varies or deviates from the mean. It gives us an idea about how spread out our data points are.
Sum of squares: The sum of squares calculates how much each score deviates from the mean by squaring those differences and summing them up.
Population variance: Population variance is used when we have information about every member (individual) within a given population.
Sample variance: Sample variance is used when we only have information about a subset (sample) of individuals within a population.