Maximum likelihood distribution for Bernoulli distribution

Estimation and statistical inference are key concepts in statistics that help us draw conclusions from data. Estimation involves using sample data to estimate population parameters, like the mean or proportion. There are two main types of estimators: point estimators, which give a single value as an estimate, and interval estimators, which provide a range of values, often in the form of confidence intervals. Statistical inference extends estimation by making broader conclusions about the population, including hypothesis testing. In hypothesis testing, we assess whether the observed data supports a specific claim about the population. Together, these tools allow statisticians to make informed decisions based on incomplete data, considering the inherent variability and uncertainty.
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