Central Limit Theorem
Explore the Central Limit Theorem to understand how the mean of large random samples approximates the population mean regardless of data distribution. Learn why this theorem is crucial for analyzing big datasets efficiently, especially in predictive data analysis, and see how it helps generalize results from sample data to entire populations using Python.
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In inferential statistics, operations are performed on a sample of data, and then predictions are made about an entire population. The central limit theorem is considered an important concept in inferential statistics due to its widely used applications.
What is it?
The central limit theorem or CLT states that:
The mean of a random sample will closely resemble the mean of the whole population as the sample size increases, regardless of the shape ...