数学希冀在生活中的应用(国外英文资料).docVIP

数学希冀在生活中的应用(国外英文资料).doc

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数学希冀在生活中的应用(国外英文资料)

数学期望在生活中的应用(国外英文资料) Mathematical expectations are applied in life Wang xiao-tong middle school Abstract: mathematical expectation is one of the most important digital features of random variables and is one of the most basic characteristics of random variables. Through several examples, this paper expounds the teaching of probability and mathematical statistics expectations in life, the application of the article content includes medical decision-making, profits, lottery, some examples, this paper expounds the mathematical expectation in the economic and practical problems of valuable applications. Keywords: random variables, mathematical expectations, probability, statistics Mathematical expectation, or mean, is an important digital feature of probability theory, which has important applications in economic management. This paper discusses mathematical expectation in the economic and practical problems of some simple applications, in order to let students understand knowledge, and close contact with the rich heritage of human practice, experience to the math really useful. Mathematical expectations of random variables: In theory of probability and statistics, the expectations of a discrete random variable (or mathematical expectation, or average, also referred to as expected) is a test of the probability of each possible outcome multiplied by the sum of the results. In other words, the expected value is the average of the same expectation that the random experiment repeats at the same opportunity. It is important to note that the expected value does not necessarily equate to the expectations of common sense -- the expectations may not be equal to each outcome. (in other words, the expected value is the mean of the output value of the variable. The expected value doesnt necessarily contain the output value of the variable.) Mathematical expectation algorithms for individual data: The definition of mathematical expectations is this. Mathematical expectation E (X) =

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