Comparing the law of large numbers with the central limit theorem, the law of large numbers is about the:

1. The two results say different things about large samples. 2. The law of large numbers says the mean of the sample tends to get closer and closer to the population mean. 3. That is a statement about where the estimate settles, that is its centre. 4. As sample sizes increase, the distribution of means more closely follows the normal distribution. 5. That second statement is about the shape of the sampling distribution. _Source: OpenStax Introductory Statistics 2e (CC BY 4.0), Ch 7 'The Central Limit Theorem', sections 7.1-7.3_