李庆海. 从数理统计学的观点来看直接观测中的一些问题[J]. 武汉大学学报 ( 信息科学版), 1957, 1(0): 34-41.
引用本文: 李庆海. 从数理统计学的观点来看直接观测中的一些问题[J]. 武汉大学学报 ( 信息科学版), 1957, 1(0): 34-41.
Li Ching-hai. SOME PROBLEMS IN THE THEORY OF ERRORS OF DIRECT OBSERVATTONS AS VIEWED FROM THE THEORY OF MATHEMATICAL STATISTICS.[J]. Geomatics and Information Science of Wuhan University, 1957, 1(0): 34-41.
Citation: Li Ching-hai. SOME PROBLEMS IN THE THEORY OF ERRORS OF DIRECT OBSERVATTONS AS VIEWED FROM THE THEORY OF MATHEMATICAL STATISTICS.[J]. Geomatics and Information Science of Wuhan University, 1957, 1(0): 34-41.

从数理统计学的观点来看直接观测中的一些问题

SOME PROBLEMS IN THE THEORY OF ERRORS OF DIRECT OBSERVATTONS AS VIEWED FROM THE THEORY OF MATHEMATICAL STATISTICS.

  • 摘要: 误差理论与最小二乘法虽然已经大约有一个世纪牛的历史了,但是当学习这用科学时,可能每人全会感到有些说理不太周密不能很好地自圆其说的地方。按作者看来,误差论(包括误差理论和最小二乘法)应当是数学的一个分枝。它应当从一些基本的假定出发,演变成一套数学理论,然后在实用中取得验证。

     

    Abstract: Probably every one of us, while studying the method of least squares, feels the lack of rigorousness in its reasoning, and is not quite satisfied with its theory.The author proposes that theory of errors(i.e. the method of least squares)should be treated as a branch of applied mathematics, and be studied in the light of probability theory and mathematical statistics. In the present time, the theory of errors has not enough connection with probability theory and mathematical statistics as it should.In this paper, the author tries to analyse some problems in direct observations of equal weights from the view-point of mathematical statistics, he examined the derivation of the law of normal distribution (Gaussian law), the definition of "true value" and "true error", introduces to the reader the ideas of population, sampling and samples, convergence, in probability, applies the ideas of consistent and unbiased estimation in estimating the population mean and population variance, and thus obtains a better derivation of Bessel's formula, points out the incorrectness of equating the true error of the mean and the mean square error of the mean.Finally, the author explains the idea of large and small samples, and the application of "Students distribution" in finding the confidence interval of the arith-matical mean.

     

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