maths.free › Probability Theory › The law of large numbers and the central limit theorem

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.

Fungerat exempel · 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}

Steg för steg

  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.

Avslöja svaret
e

Nu är det din tur. Välj ett problem, skriv eller rita ditt eget. Varje steg, en bild, svaret dolt tills du frågar.

Fortsätt jobba.

Ett gratis konto lägger till anteckningar om varje lektion, en förteckning över vad du har avslutat, dina lösta problem på ett ställe, och en handledare du kan fråga om denna sida. Matematiken i sig är öppen för alla, inloggad eller inte.

Registrera dig Inloggning

Symboler som används här

Knacka på alla symboler för den fullständiga definitionen, en bild, och vad varje bokstav i den betyder.

Hur man: 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.

Frågor folk frågar

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.

Mer information Probability Theory

Sample spaces and the axiomsRandom variables and expectationThe common distributions