RMS value + root mean square error (RMSE) + standard deviation (Deviation)
1, RMS,also known as the validity , It is calculated by first square, then average, and then the root.
2. Root mean square error, It is the square root of the squared and observed n ratios of the observed and true values, in the actual measurement, the number of observations n is always limited, the true value can only be used for the most reliable (best) values to substitute The square root error is very sensitive to the large or small errors in a set of measurements, so the RMS error can well reflect the precision of the measurement. the RMS error, when measured in a certain amount, takes the RMS difference of true error of the measurement column (the arithmetic mean of true error squared again), called the standard deviation, expressed in σ. Σ reflects the degree to which the measured data deviates from the true value, the smaller the σ, the higher the accuracy of the measurement, so σ is used as a criterion for measuring the accuracy of this measurement process.
3, Standard deviation (Deviation), the standard deviation is the arithmetic square root of the variance, also known as the mean variance (mean square error), is the average distance from the average deviation of the data, which is the square root of the squared and average deviations, and the standard deviation
can reflect the degree of dispersion of a data set , expressed in σ.
RMS + root mean square error (RMSE) + standard deviation (Deviation)