Where x represents the average of samples, n represents the number of samples, xi represents individuals, and S 2 represents variance.
Square difference: a? -B? =(a+b)(a-b). Text expression: The product of the sum of two numbers and the difference of two numbers is equal to the square of the difference of two numbers. This is the square difference formula.
Standard deviation: standard deviation = sqrt ((x1-x) 2+(x2-x) 2+... (xn-x) 2)/n). Is the square root of the arithmetic mean of the mean square deviation, expressed by σ. It is most commonly used in probability statistics as a measure of statistical distribution. The standard deviation is the arithmetic square root of variance. The standard deviation can reflect the degree of dispersion of the data set.
Extended data:
Variance and standard deviation are the most important and commonly used indicators to measure discrete trends. Variance is the square of variance of each variable value and the average of its mean, which is the most important method to measure the dispersion degree of numerical data. The standard deviation is the arithmetic square root of variance, expressed by S.
Standard deviation can be used to measure uncertainty. For example, in physical science, when repeated measurements are made, the standard deviation of the set of measured values represents the accuracy of these measurements. When determining whether the measured value conforms to the predicted value, the standard deviation of the measured value plays a decisive role: if the measured average value is too far from the predicted value, it is considered that the measured value is contradictory to the predicted value.
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