This course covers the learning outcomes and goals of understanding Maximum Likelihood Estimator (M.L.E) topics, including M.L.E of gamma distribution, Bernoulli distribution, exponential distribution, and geometric distribution. The course teaches the skills of calculating M.L.E for different distributions and parameters. The teaching method involves theoretical explanations and practical examples. The intended audience for this course is individuals interested in statistics and probability theory.
Overview
Syllabus
M.L.E of gamma distribution.
M.L.E of Bernoulli distribution or (point binomial ).
M.L.E of exponential distribution both cases for beta and theta.
Maximum likelihood estimator of "P" for geometric distribution 1. n experiments are performed.
Taught by
Statistics is Fun A.H
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