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在概率学习中,事件的互不相容与相互独立是两个十分重要的概念,也是计算概率的重要工具.为了更好地掌握这一对概念,本文结合教学实践,对它们之间的区别和联系做进一步较深入的讨论。 相似文献
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<正>在学习了古典概型后,许多学生虽然尚未学习互相独立事件积的概率,却往往会从生活经验出发,利用事件概率的积来计算一些"看似没有关联"的事件积的概率.比如,用1/6×1/6计算连续掷一颗骰子两次都得到6的概率.即使在学习了互相独立事件的概念后,由于上海现行高中教材缺少条件概率的内容,学生也往往无法真正理解事件独立性的内涵,而将互相独立事件积的概率运算公式错误地推广到许多其他问题. 相似文献
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借助于条件数学期望和随机事件A的示性函数IA,通过对随机变量的适当"条件化"处理,应用全期望公式和推广的全概率公式,讨论了计算数学期望和概率的条件化方法. 相似文献
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本文利用概率母函数法给出了 Consecutive-k-out-of-γ-from-n:F系统的可靠性精确解.这种方法适用于较复杂的系统可靠性计算,易于在计算机上实现. 相似文献
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如所周知,n个互不相容的事件和的概率等于各个事件的概率之和。在一般情形,当A_1,A_2,…,A_n可以是相容的,为求和■A_i的概率,我們有如下的公式(参看[1]的第一章习題20):当n=1时,公式显然成立;当n=2时,也是容易証明的,因为 相似文献
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在运用概率的加法公式和乘法公式的计算时,由于教师对于学生关于事件的互不相容和事件的相互独立这两个容易混淆的概念未予重视。因而学生在解题过程中往往出现错误,教师有必要及时对这些错误进行剖析,分析产生错误的原因。这对于培养学生正确、合理的解 相似文献
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Communicated by D.R.Brown 相似文献
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基于学习—遗忘效应的生产率降低损失索赔研究 总被引:1,自引:0,他引:1
建设工程项目很多具有重复性施工的特点,本文利用这种特点将学习-遗忘效应应用到平衡作业线(LOB)方法中,分析因为工程中断造成生产率的降低的现象,认为因生产率降低而导致工程工期的延长实际上超过工程实际中断的时间,最后以一个工程案例来说明分析过程. 相似文献
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J. Donald Monk 《Mathematical Logic Quarterly》2012,58(3):159-167
We give some results concerning various generalized continuum cardinals. The results answer some natural questions which have arisen in preparing a new edition of 5 . To make the paper self‐contained we define all of the cardinal functions that enter into the theorems here. There are many problems concerning these new functions, and we formulate some of the more important ones. 相似文献
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Xu Mingwei 《数学学报(英文版)》1994,10(2):143-148
We give a treatment of the Weiertrass points of curves which is a little different from the treatment by Laksov. We introduce
the notion of theith weight which makes the treatment easier and gives an algorithm for computing the gap sequence of an effective divisor and
the weight at a point.
Supported in part by NNSF of China. 相似文献
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Rendiconti del Circolo Matematico di Palermo Series 2 - A closed densely defined operatorT on a Banach spaceX is called normal, iff $$T \in [C^0 (\hat \not C)]$$ , i.e. there is a homomorphism... 相似文献
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R. V. Ambartzumian 《Probability Theory and Related Fields》1976,37(2):145-155
Every c-finite measure Μ on the set G of the lines on the plane such that $$(0){\text{ }}\mu {\text{(\{ g}} \in G:{\text{ }}P \in {\text{g\} ) = 0}}$$ for every point P?R 2 generates a pseudo-metric F on the plane when one puts F P 1, P 2= \(\tfrac{1}{2}\) μ({g∈G:g separates the points P 1 and P 2}) The pseudo-metrics which are generated in this way possess the property of linear additivity, that is F(P 1,P 3)=F(P 1,P 2)+F(P 2,P 3) for P 1,P 2,P 3 on a line, P 2 between P 1 and P 3, and are continuous with respect to the Euclidean topology in R 2 × R 2. In this paper we prove the converse: every linear additive and continuous pseudo-metric F is generated as above by some c-finite measure Μ on G for which (0) holds. The method of proof shows that values of linearly additive and continuous pseudo-metric F inside every bounded convex polygon C are determined completely by the values of F on (δC)2. The representation of pseudo-metrics by measures is useful in derivation of inequalities for the former. 相似文献
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