What is the total of squared deviations from the mean?

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Multiple Choice

What is the total of squared deviations from the mean?

Explanation:
The total of squared deviations from the mean is called the sum of squares. For each data point, you measure how far it is from the mean, square that distance, and add all those squared distances together. That overall sum, often denoted SS, represents the total variability around the mean. Variance is the next step: it’s the average of those squared deviations (SS divided by n for a population, or by n-1 for a sample). The standard deviation is just the square root of that variance. Degrees of freedom is a separate concept that counts the number of independent pieces of information used to compute the statistic, not a sum of squared deviations. So the total of squared deviations from the mean is the sum of squares.

The total of squared deviations from the mean is called the sum of squares. For each data point, you measure how far it is from the mean, square that distance, and add all those squared distances together. That overall sum, often denoted SS, represents the total variability around the mean.

Variance is the next step: it’s the average of those squared deviations (SS divided by n for a population, or by n-1 for a sample). The standard deviation is just the square root of that variance. Degrees of freedom is a separate concept that counts the number of independent pieces of information used to compute the statistic, not a sum of squared deviations.

So the total of squared deviations from the mean is the sum of squares.

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