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Maximum Likelihood Estimation

Edited by: Published: 2017
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Maximum likelihood estimation (MLE) provides a means of estimating the sum value by using the parameters that “maximize” the agreement between the selected model and the observed data. In the case of data that meet the normal curve, a well-defined model provides a good method to make estimations. The question of providing a general statistical and/or theoretical model serves as the basis of a comparison between the observed values and the ones expected by the model.

Suppose a set of observations is collected using some form of measurement, like scores for public speaking anxiety across a sample of participants. The approach assumes that each of the observations are independent and operate within some model. If the model is assumed or believed to represent ...

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