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Sampling Distribution And Approximations Of Distributions:
1) Learnt three approaches for deriving the probability distributions of functions of one or more random variables viz. the methods of cdf pdf and mgf
2) Been introduced to the theoretical primary of special probability distributions in which play significant role in the theory of statistical inference which you will learn in the next Block. These are X2 F and t distribution.
3) Been introduced to the X2, F and t distribution tables.
4) Been prepared for learning statistical inference in which is the subject matter of remaining blocks by introducing to you the concept of random sample, statistic and its sampling distribution.
5) Learnt the importance and use of weak law of large numbers.
6) Learnt the significance of central limit theorem.
7) Learnt to approximate binomial, Hypergeometric, Poisson, distribution through normal distribution with the help of central limit theorem.
Compare the probabilities: Use the central limit theorem to compute P (¦ X - μ ¦ ≥ k), k = 1, 2,3,4,5 where X and μ are as defined in Example. Compare the probabilities with t
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