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Foxglove
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Can someone help please? are these statements true or false? With some proofs.
Maximum Likelihood is a statistical method used to estimate the parameters of a probability distribution by finding the values that maximize the likelihood of the observed data.
No, Maximum Likelihood is not always the best method for parameter estimation. It may not be suitable for small sample sizes or when the data does not follow a specific distribution.
Yes, Maximum Likelihood can be used for both continuous and discrete data. It is a versatile method that can be applied to various types of data.
The likelihood function is a key component in Maximum Likelihood as it represents the probability of observing the data given the parameters of the distribution. The goal of Maximum Likelihood is to find the values of the parameters that maximize this likelihood function.
Yes, there are mathematical proofs that show that under certain conditions, Maximum Likelihood provides the most accurate estimates of the parameters. These conditions include having a large sample size and the data following a specific distribution.