- 更多网络例句与数学随机样本相关的网络例句 [注：此内容来源于网络，仅供参考]
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Events,Operation and Relation of Sets, Classical Probability, Geometrical Probability , Statistical Stability of a Frequency, Axioms of Probability, Conditional Probability, Total Probability Theorem, Bayes' Rule,Independent Events,Independent Repeated Trials, One Dimensional Random Variables, Discrete Random Variables, Distribution Function of a Random Variables , Continuous Random Variables, Normal Distribution, Distribution of a Function of a Random Variable, Multidimensional Random Variables, Joint Distribution Function, Marginal Distribution Function,Discrete Two—Dimensional Random Variables,Continuous Two—Dimensional Random Variables, Independent Random Variables, Distribution of Functions of Random Variables,Expectation,Variance, Covariance, Coefficient of Correlation, Bivariate Normal Distribution, Law of Large Numbers, The Central Limit Theorems, Sample and Population ,Chi—Squared, T and F Distributions , Sampling Distributions , Point Estimation , Interval Estimation , Testing Hypotheses , A Test of Significance for Parameters in a Single Sample From a Normally Distributed Population , A Test of Significance for Parameters in Two Sample From Normally Distributed Populations .
本课程的主要内容：概率的概念与运算、随机变量及其分布、随机变量的数字特征与极限定理、数理统计的基本概念、估计和检验的基本方法，随机事件与概率随机事件、事件的关系与运算、几何概率、统计概率等，条件概率、全概率公式、贝叶斯公式、事件的独立性、二项概率公式，随机变量的概念、离散型随机变量、随机变量的分布函数、连续型随机变量、随机变量函数的分布，多维随机变量及其分布函数、边缘分布函数、随机变量的独立性、二维随机变量函数的分布，数学期望、方差、协方差和相关系数、大数定律、中心极限定理，总体与样本， X 2-分布、 t-分布和 F-分布，统计量及抽样分布，假设检验的基本概念、单个正态总体参数的显著性检验、两个正态总体参数的显著性检验。
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One approach, from mathematical point of view, is to translate the test into comparson of the constant a and proportion b of linear regression by using F test .
数学上该问题转化为对回归直线的常数 a和比例系数 b两组随机样本的 F检验。
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To build a model of this kind, a nonstationary random process mathematical model is set up through fast Fourier transformation and Herbert transformation based on available original records, and random samples are produced by numerical simulation.
该方法根据有限的原始风速记录，通过快速富氏变换和希尔伯特变换，建立了非平稳随机过程数学模型，然后以数字模拟的方法产生所需的随机样本。
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Using it we can approximately obtain the expectation of any function,using the certain quantity the random sample particle to express the posterior density of random variable in the model,and can be used in the any non-linear random models.
粒子滤波算法是一种适用于非线性非正态约束的基于模拟的统计滤波算法，可以近似得到任意函数的数学期望，利用一定数量的随机样本粒子来表示模型中随机变量的后验概率分布，并且能应用于任意非线性随机模型。
- 更多网络解释与数学随机样本相关的网络解释 [注：此内容来源于网络，仅供参考]
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mathematical random sample：数学随机样本
mathematical programming 数学规划 | mathematical random sample 数学随机样本 | mathematical statistics 数理统计