enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Central_limit_theorem

    If this procedure is performed many times, resulting in a collection of observed averages, the central limit theorem says that if the sample size is large enough, the probability distribution of these averages will closely approximate a normal distribution. The central limit theorem has several variants.

  3. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    Sample size determination or estimation is the act of choosing the number of observations or ... including the law of large numbers and the central limit theorem.

  4. Galton board - Wikipedia

    en.wikipedia.org/wiki/Galton_board

    Galton box A Galton box demonstrated. The Galton board, also known as the Galton box or quincunx or bean machine (or incorrectly Dalton board), is a device invented by Francis Galton [1] to demonstrate the central limit theorem, in particular that with sufficient sample size the binomial distribution approximates a normal distribution.

  5. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    1.4 Independent and identically distributed random variables with random sample size. 2 Student approximation when ... in light of the central limit theorem. ...

  6. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    Because of the central limit theorem, many test statistics are approximately normally distributed for large samples.Therefore, many statistical tests can be conveniently performed as approximate Z-tests if the sample size is large or the population variance is known.

  7. Law of large numbers - Wikipedia

    en.wikipedia.org/wiki/Law_of_large_numbers

    The limit e it μ is the ... With this method, one can cover the whole x-axis with a grid (with grid size 2h) ... Central limit theorem; Infinite monkey theorem;

  8. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    11.4 Showing consistency using the central limit theorem. 12 See also. 13 References. 14 ... likelihood estimator have good performance when the sample size is ...

  9. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    By the central limit theorem, sample means of moderately large samples are often well-approximated by a normal distribution even if the data are not normally distributed. However, the sample size required for the sample means to converge to normality depends on the skewness of the distribution of the original data.