The central limit theorem is basic to the concept of statistical inference because it permits us to draw conclusions about the population based strictly on sample data.

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The central limit theorem is a fundamental concept in statistics because it enables us to use statistical inference techniques to draw conclusions about the population based on sample data. The theorem states that, under certain conditions, the distribution of sample means approaches a normal distribution as the sample size increases, regardless of the distribution of the population from which the sample is drawn. This property allows us to make probabilistic statements about population parameters based on sample statistics, and it forms the basis for many statistical tests, such as hypothesis testing and confidence interval estimation.

The Central Limit Theorem Is Basic to the Concept of Statistical