👉 Unbiasedness is a property of an estimator or statistic that ensures its value is not affected by how it was generated. In other words, an unbiased estimator is one that always gives the same result when applied to data from any distribution, regardless of the underlying probability distribution. This means that the estimator will give the same answer as if it were calculated under a uniform distribution across all possible outcomes. For example, consider an estimator for a population mean (e.g., sample average) such as the sample
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What is the definition of Unbiasedness? 🙋
👉 In statistics, "unbiasedness" refers to a property of a statistical estimator or statistician that ensures the estimator is always equal to its mean value. This means that if you take an unbiased estimator and apply it to a random sample from a population, the result should be exactly as expected by chance. For example, suppose we have a population with 100 people and want to estimate the average age of these individuals. If we use a simple random sample (SRS) to select
