central_limit_theorem

introduction

%%visits: 3 ## intuition A series of probability_density_functions eventually becomes a normal probability_density_function. ## rigour

Let X₁, X₂, … be independent and identically distributed random_variables with 𝔼(x_i) = μ and var(X_i) = σ² < ∞

$$ Z_n `:=` \frac{\sum _{k=1}^{n} X_k - n\mu}{\sigma \sqrt{n}} = \frac{\overline{X} - n \mu}{\frac{\sigma}{\sqrt{n} }} $$ ## exam clinic ## examples and non-examples ## resources tags :math:

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