面向能力培养的教学模式探讨——以工科概率统计课程为例

以工科概率统计课程为例探讨面向能力培养的教学模式.概率统计是高等院校工科专业一门重要的公共基础课程.文章分析了概率统计课程的教学现状,指出其在教学理念、教学方法上必须进行适度改革,以深化其教育功能;分析了概率统计教学平台在培养学生能力上的不可替代的重要作用;探讨了落实概率统计课程教育功能可以采取的教学方法.     

索赔额是指数分布的马氏风险模型的破产概率

本文研究了马氏风险模型的破产概率,在索赔额服从指数分布或混合指数分布情形,通过解破产概率所满足的微积方程组,给出了破产概率的解析表达式.     

概念图——概率统计教学的新途径

简述了概念图的起源、国内外发展现状,介绍了概念图的三个组成部分:结点、连线和连接语词,指出了相对于传统教学的概念图教学,在概率统计教学中的突出之处:概念图可作为教师教学的先行组织者;可作为学生复习时整理知识的工具;可作为教师检测学生学习的工具,提出了概率统计知识概念图制作的策略,并用实例说明了概念图应用于概率统计教学中的良好效果.     

用数形结合法求解连续型随机变量的函数分布问题

针对概率统计课程教学中的关于"连续型随机变量函数的分布"这类难点,利用数形结合的思想,巧妙的通过一副图形完全涵盖了这一类问题所需的概率知识点,且帮助了学生后续积分的计算.表明数形结合法是一个值得在概率统计教学中推广的好方法.     

利用人工智能案例推动概率统计课程教学

人工智能的迅猛发展离不开概率统计的支持,在概率统计的日常教学中,融入人工智能案例的介绍,能够促进学生的学习兴趣,提高教学质量.以举例的方式说明了概率统计的理论知识和人工智能技术的结合,为利用人工智能案例推动概率统计的课程教学提供了示例.     

索赔额服从亚指数分布族S~*的破产概率研究

研究了亚指数分布族中一类特殊的分布,在年索赔额服从该特殊分布的假设下,推导出了的终极破产概率的渐进表达式,提出了可以用随机模拟方法对于服从亚指数分布的破产概率进行模拟计算的方法.从实践的角度来说,更具有可操作性,为保险业提供了一些应对极值概率事件的理论依据和检验方法.     

浅谈工科概率统计的教学方法

如何提高概率统计课程教学质量,增强工科学生对概率统计方法的理解及应用能力已成为现代工科数学教学的一个重要课题.结合多年的教学实践,本文提出了对概率统计教学的几点认识.     

课改后统计与概率内容考查研究

1 引言 统计与概率在工农业生产和社会生活中有着广泛的应用.在生产、生活和科学技术飞速发展的当今社会,它的应用已渗透到整个社会的方方面面,从而使统计与概率的基础知识成为一个普通公民的必备常识.由于统计与概率的学习对于培养和提高学生的数学思维能力方面发挥着特有的作用,因此国外许多国家很早就将其列为中、小学数学教学的内容和目标的一部分.如美国在1989年出版《中小学数学课程与评估标准》中规定了统计与概率,并且强调统计和概率的思想方法[1];前苏联在1990年颁布的教学大纲中就包涵概率与统计理论的教学内容,包括概率的加法与乘法,条件概率,独立事件,伯努利公式,随机变量,数学期望等内容知识.     

指数分布抽样基本定理及在指数分布参数统计推断中的应用

发现指数分布抽样基本定理,应用到指数分布参数的统计推断中,得到了指数分布参数的一致最小方差无偏估计;并且得到了单总体指数分布参数的置信区间及联合置信区间,以及双总体指数分布参数比值及差的置信区间.     

基于SPOC的概率统计课程建设研究

基于SPOC的教学模式结合了MOOC教学与传统教学,为当代教学改革提供了新思路.本文以概率统计课程为例,分析概率统计课程教学的现状,探讨SPOC教学模式的设计流程,提出概率统计课程改革的新思路和遇到的困难,分析该教学模式在提高教学质量的同时,对教师和学生提出更高的要求.     

A modified power series distribution

Summary A modification of the usual power series distribution is proposed and a statistical treatment of data generated by this probability model is indicated. It is shown that this modified power series distribution belongs to a multiparameter discrete exponential family and standard theory is then applied to obtain complete sufficient statistics of the parameters, sampling distribution of these statistics, maximum likelihood and minimum variance unbiased estimators, uniformly most powerful unbiased tests, uniformly most accurate confidence intervals and expected cover tolerance regions. CSIRO, Division of Mathematical Statistics     

Inequalities for order statistics of samples from distributions with monotone hazard rate

A number of inequalities relating the mathematical expectations of order statistics or functions of order statistics in the case where the sample is taken from a distribution with monotone hazard rate function are presented. These inequalities can be applied in reliability theory and other areas of probability theory and mathematical statistics. In particular, in the paper, they are used to obtain new characterizations of the exponential distribution.     

On families of distributions characterized by certain properties of ordered random variables

In this work, we obtain new characterizations of certain probability distributions by relations with different ordered random variables. Such variables include order statistics, sequential maxima, and records. We consider relations that include not only upper, but also lower record values. The presented ordered objects are based on sequences of independent random variables with a common continuous distribution function. We also investigate equalities in the distribution of sequential maxima exposed by various random shifts. These shifts (one-sided or two-sided) have exponential distributions. Certain theorems and their corollaries present corresponding characterizations of distributions by relations of such a type. In addition, we consider exponentially shifted order statistics such that simple relations among them also characterize certain probability distributions. All of the presented results yield a set of characterizations of various distributions. For particular cases, we present the relations that characterize families of classical exponential and logistic distributions.     

注重统计思想的现代工科概率统计教学方法

指出了工科概率统计教学中长期存在而又被忽视的一个问题,即学生的统计计算能力有余而对于统计思想、统计方法的理解与使用不足.并尝试着提出了注重统计思想的现代统计教学方法.     

概率论与数理统计实验教学案例设计

为克服传统数学教学模式局限于理论教学的弊端而倡导实践教学,设计出一个概率论与数理统计实验教学的案例,将线性回归分析应用于高光谱遥感图像的处理之中.     

Differential geometry of edgeworth expansions in curved exponential family

Summary In order to construct a higher-order asymptotic theory of statistical inference, it is useful to know the Edgeworth expansions of the distributions of related statistics. Based on the differential-geometrical method, the Edgeworth expansions are performed up to the third-order terms for the joint distribution of any efficient estimators and complementary (approximate) ancillary statistics in the case of curved exponential family. The marginal and conditional distributions are also obtained. The roles and meanings of geometrical quantities are elucidated by the geometrical interpretation of the Edgeworth expansions. The results of the present paper provide an indispensable tool for constructing the differential-geometrical theory of statistics.     

把计算机引入概率统计课教学的探讨与实践

把计算机引入概率统计课教学的探讨与实践＠赵学慧＠李喜军￥吉林化工学院把计算机引入概率统计课教学的探讨与实践赵学慧李喜军（吉林化工学院，吉林１３２０２２）随着教学改革的不断深入，改革传统的教学方式，采用多媒体组合进行教学已提到日程上来．在高科技蓬勃发展的今天...     

Modeling and linking the Poisson and exponential distributions

Randomness and distribution are important concepts underpinning the ability to think and reason probabilistically. Traditional approaches to teaching the Poisson distribution focus on mathematical definitions and formulae which obscure the randomness intrinsic in this process. Advances in technology have made it possible for students learning about probability to model the Poisson process. In this paper we explore the reasoning of six introductory probability students as they interacted with a prototype software designed to visibilize randomness, and to make transparent the link between the Poisson and exponential distributions. We focus on a task involving both real data and simulated data. Our findings highlight the fact that the tool and tasks seem to help students’ understanding of the link between the Poisson and exponential distributions, and to gain a deeper appreciation of distribution and randomness.