반응형 Statistics48 Independence of Sample Mean and sample Variance of Normal distribution. I want to prove that when random samples X1,X2,...,Xn independent and identically follows Normal distribution with mean μ and variance σ^2, the sample mean and the sample variance of the samples are independent. This is regarded as a crucial fact when proving one of the properties of T distribution. Which is when x1,x2,x3,...,xn are from the normal distribution with mean μ and variance σ^2, n^0... 2020. 10. 26. Bayesian Statistics Bayesian Statistics is the way to update the information about any distribution with prior information after observation.That is, It allows us to form posterior distribution which includes every information about the parameter by using conditional probability. And the conditional probability might be familiar with you if you studied about the Bayes Theorem before.The thing you should know is tha.. 2020. 10. 25. Cdf technique We can define the relationship of distributions and the property of distribution by using Cumulative distribution function, which is easily called cdf, F(X=x). In probability, Cumulative distribution function is the probability that X will take a less or equal value to a real value x, which can be expressed as P(X 2020. 10. 21. MGF Technique We can define the relationship of distributions and the property of distribution by using properties of Moment generating functions. The main reason which makes it possible is that the moment generating functions are unique for each distribution. So If we know the moment generating function, there should be only distribution which correspond to the MGF. Let me give you some typical relationships.. 2020. 10. 17. 이전 1 ··· 3 4 5 6 7 8 9 ··· 12 다음 반응형
