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Sampling and Sampling Distributions

Sampling involves selecting a subset of data from a population to estimate characteristics of the whole population.

Sampling Distribution​

The sampling distribution is the probability distribution of a statistic (such as the sample mean) obtained from a large number of samples drawn from a specific population.

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Central Limit Theorem​

The central limit theorem states that the sampling distribution of the sample mean will approximate a normal distribution, regardless of the shape of the population distribution, provided the sample size is sufficiently large (usually n=30n = 30).

Xˉ∼N(μ,σ2n)\bar{X} \sim \mathcal{N}(\mu, \frac{\sigma^2}{n})

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