课程: Probability Foundations for Data Science

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Normal approximation of the binomial distribution

Normal approximation of the binomial distribution

课程: Probability Foundations for Data Science

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Normal approximation of the binomial distribution

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- [Instructor] Let's wrap up with the normal approximation of the binomial distribution. The normal approximation of the binomial distribution is a useful technique in probability, that allows you to use the normal distribution, to approximate the binomial distribution under certain conditions. This approximation will simplify calculations, especially for large sample sizes. Remember, the binomial distribution describes the number of successes, in a fixed number of independent Bernoulli trials, each with the same probability of success. It is represented by the following probability mass function, where it has case successes. So in this case, how large is large enough? The normal approximation to the binomial distribution can be used when the sample size n is large enough such that both the expected number of successes and failures are sufficiently large. A common rule of thumb, is that the approximation is reasonable if n multiplied by p is greater than or equal to 10 and n…

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