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The next topic is completeness, a property that ensures parameters of a probability distribution can be estimated based on sample statistics. Completeness allows for estimation of different parameter values within a family of distributions. The statistic theta cap is a measurable function of sample values, important for the measurability in statistics. For every measurable function h independent of theta, the expected value being 0 implies the probability of events where h is 0 is equal to 1. This can also be written as the function's value being 1.
