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The Central Limit Theorem
The theories was introduced by De Moivre and according to it; if we choose a large number of simple random samples, says from any population and find out the mean of each sample, the distribution of these sample means will tend to be described by the common probability distribution along with a mean µ and variance σ2/n. It is true even if the population itself is not normal distribution. Or the sampling distribution of sample means approaches to a normal distribution irrespective of the distribution of population from whereas the sample is consider and approximation to the normal distribution becomes increasingly close along with increase in sample sizes
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We can define the conditional probability of event A, given that event B occurred when both A and B are dependent events, as the ratio of the number of elements common in both A an
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Surface Area- Applications of integrals In this part we are going to look again at solids of revolution. We very firstly looked at them back in Calculus I while we found the
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Combined Mean And Standard Deviation Occasionally we may need to combine 2 or more samples say A and B. Therefore it is essential to identify the new mean and the new standard
Q. What is Uniform Distribution? Ans. A distribution is the set of possible values of a random variable considered in terms of their theoretical or observed frequency. Th
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