In a given score distribution of 12, 14, 16, 18 and 20, the sum of square deviation is:

Correct option is C

The sum of square deviations for the given score distribution of 12, 14, 16, 18, and 20 is 40. The sum of square deviations is a measure of the total variation in a set of data points around the mean, which is crucial for calculating variance and standard deviation.
Information Booster:
1. Sum of Square Deviations: This is calculated by taking each score, subtracting the mean, squaring the result, and then summing these squared differences.
2. Mean of the Distribution: For the given scores (12, 14, 16, 18, 20), the mean is 16.
3. Variance: The variance is obtained by dividing the sum of square deviations by the number of observations (for population variance) or by n−1n-1n−1 (for sample variance).
4. Standard Deviation: The square root of the variance gives the standard deviation, a measure of how spread out the numbers in the data set are.
5. This measure is important in statistics to understand the dispersion and variability within a data set.
Key Points:
· The sum of square deviations is a fundamental concept in statistics, forming the basis for calculating variance and standard deviation.
· Understanding how to calculate and interpret these measures is crucial for analyzing data and understanding the distribution of scores in any data set.
· This concept is widely used in various statistical analyses, including hypothesis testing and regression analysis.