How to Determine Sample Size for Central Limit Theorem?

Thread starter moonman239
Start date Jul 11, 2011
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Central limit theorem Limit Sample size Theorem

AI Thread Summary

To determine the sample size for the Central Limit Theorem (CLT) to apply, it is essential to consider the distribution of the data. A common rule of thumb suggests that a sample size of around 30 is generally sufficient for the distribution of the sample mean to approximate normality. However, this is not a strict calculation and can vary based on the underlying distribution characteristics. The Berry-Esseen theorem can provide additional insights into how quickly the distribution of the sample mean converges to normality. Understanding these principles is crucial for accurate statistical analysis.

Jul 11, 2011

moonman239

Is there a way to calculate/estimate how big a sample from a parent distribution would need to be for the distribution of the mean of that sample to be approximately normally distributed?

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Jul 11, 2011

MaxManus

You can't just calculate it, it depends on the distribution of the data. But about 30 is the rule of thumb.

Jul 11, 2011

bpet

The Berry-Esseen theorem may be useful here.

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