Wimbledon 2010: A Fifth Set Cliff‐hanger in the Murray vs. Federer Final?

Imagine the scene. The year is 2010 and Andy Murray and Roger Federer are playing each other for the first time in the Wimbledon Championships final. Will it be a straight sets victory or a nail‐biting five‐set match?     

关于或有事项若干问题的分析

或有事项作为特殊的不确定性事项，是不确定性会计的重要内容。或有事项的确认和披露是当前会计理论和实务中的一大难点。要正确理解和运用财政部发布的《企业会计准则——或有事项》，必须明确或有事项与未来事项、估计事项及资产负债表日后事项的区别；正确理解负债、预计负债和或有负债之间的关系；正确区分或有事项的各种可能性及其会计处理；正确核算因或有事项确认的负债及相关的资产。     

概率论与数学分析知识的相互运用

通过一些实例讨论了数学分析方法在概率论中的运用,以及数学分析中的一些问题也可用概率论的方法去解决.     

Probability with Roulette

This article describes how roulette can be used to teach basic concepts of probability. Various bets are used to illustrate the computation of expected value. A betting system shows variations in patterns that often appear in random events.     

室内^222Rn/^220Rn浓度分布的CFD模拟

室内^222 Rn/^220 Rn危害的评估与防护中,^222 Rn/^220 Rn浓度水平与空间分布的准确计算是一个关键问题。通过对室内^222 Rn/^220 Rn水平影响因素的分析,建立较真实的物理模型,运用CFD技术研究固定外界^222 Rn/^220 Rn浓度与壁面析出率时,不同通风状况下室内^222 Rn/^220 Rn浓度的平均值与三维分布情况。     

高校学生课程满意度的统计分析——以《概率论与数理统计》课程为例

以问卷调查所获得数据为依据,采用SPSS软件包对基础数据进行处理。分别从描述性统计和因子分析的角度进行研究,比较了各指标的平均满意度,对原来12项指标进行了化简,得到了学生的综合满意度,并进行了排序。结果表明,学生的兴趣差异较大,不同性别,不同专业学生的满意度存在一定差异。     

热力学第二定律的统计意义

势力学第二定律具有极广泛和深远的意义。本文从几率概含入手讨论热力学第二定律的微观本质。     

全概率公式教学方法研究

全概率公式是概率教学中的一个难点,在概率计算中,有时要综合利用加法公式和乘法公式才能解决问题,这就是全概公式。对于一个较复杂的事件B,使用全概率公式的关键就是能找到一个伴随着B发生的完备事件组A1,A2％…An将所讨论的事件划分为若干个互不相容的“简单”事件,而这些“简单”事件的概率又相对较容易求,进而即可得最后结果。本文通过对一些典型韪的分析研究,归纳总结出求解此问题的分析方法、解题步骤,以使学生理解、掌握全概率公式,并更好地运用它解决 实际问题。     

黑龙江省玉米品种布局的农业气候依据

根据玉米分期播种资料,得出不同品种播种到出苗,出苗到抽雄及抽雄到成熟的热量指标,以地区热量资源的满足程度确定其成熟度及成熟概率。根据不同品种的成熟概率及收益状况,利用概率决策方法确定地区的主栽品种以及利用线性规划的方法求解不同品种最佳搭配的比例,从而为充热量指标;概率决策;线性规划     

Individual and field citation distributions in 29 broad scientific fields

Using an initial dataset consisting of 18.5 million distinct authors and 15 million distinct articles published in the period 2000–2016, which are classified into 29 broad scientific fields, we search for regularities at the individual level for very productive authors with citation distributions of a certain size, and for the existence of a macro-micro relationship between the skewness of a scientific field citation distribution and the characteristics of the individual citation distributions of the authors belonging to the field. Our main results are the following three. Firstly, although the skewness of individual citation distributions varies greatly within each field, their average skewness is of a similar order of magnitude in all fields. Secondly, as in the previous literature, field citation distributions are highly skewed and the degree of skewness is very similar across fields. Thirdly, the skewness of field citation distributions is essentially explained in terms of the average skewness of individual authors, as well as individuals’ differences in mean citation rates and the number of publications per author. These results have important conceptual and practical consequences: to understand the skewness of field citation distributions at any aggregate level we must simply explain the skewness of the individual citation distributions of their very productive authors.