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The law of large numbers and the central limit theorem

Why averages converge and why they are normally distributed.

The law of large numbers: sample means converge to the expectation. The central limit theorem: their fluctuations, scaled by √n, are normal. Picture it: the histogram of averages narrowing and turning bell-shaped as n grows. Think it: the CLT is a fixed-point statement. The normal is the distribution that sums of itself leave unchanged.

Contoh yang dikerjakan · limit of (1 + 1/n)^n as n -> oo

Calculus · Limits

Limit of (1 + 1/n)^n as n → oo

\lim_{n \to \infty} \left(1 + \frac{1}{n}\right)^{n}

Langkah demi langkah

  1. \lim_{n \to \infty^+-} \left(1 + \frac{1}{n}\right)^{n}

    Try direct substitution first.

  2. \

    As x grows without bound, compare the fastest-growing terms (or divide top and bottom by the highest power).

  3. = e

    Take the limit.

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e

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Bagaimana untuk: The law of large numbers and the central limit theorem

  1. Try direct substitution first.
  2. As x grows without bound, compare the fastest-growing terms (or divide top and bottom by the highest power).
  3. Take the limit.

Soalan yang orang tanya

What is the difference between probability and statistics?

Probability goes from a known model to what the data should look like; statistics goes from data back to the model. Probability theory is the deductive half.

What does the law of large numbers promise?

That the average of many independent samples converges to the expected value. It says nothing about any single trial.

Lebih dalam Probability Theory

Sample spaces and the axiomsRandom variables and expectationThe common distributions