Statistical inference usually measures the estimation accuracy by two indicators: Confidence coefficient and bias, but when confidence coefficient and bias are different, the comparison of accuracy between estimators will be difficult. In this paper, a widely used dimensionless accuracy statistic is proposed. The function of confidence coefficient and bias can compare the accuracy when the estimation bias and the degree of confidence are different at the same time. In addition, starting from the factors affecting the interpretation accuracy and its action mechanism, the logical consistency between the sample size determination formula and the Shannon theorem of information theory is found. A new explanation of the physical meaning of the sample size determination formula is given.