EasyDeepLearn

Chi-square goodness-of-fit test — setup.

medium

Answer

  • Tests whether observed frequencies match an expected distribution: χ2  =  Σ{\chi}^{2}\; = \;{\Sigma} (Oi    Ei)2  /  Ei(O_{i}\; - \;E_{i})^{2}\; / \;E_{i}, df = k - 1 - (parameters estimated).
  • Uses: is a die fair?
  • Does a dataset follow Poisson?
  • Requires EiE_{i} ≥ 5 (aggregate small buckets).
  • Modern alternatives: G-test (likelihood ratio), Kolmogorov-Smirnov (continuous), Anderson-Darling (heavier weight on tails).
Check yourself — multiple choice
  • Only for continuous data
  • χ2{\chi}^{2} test that observed frequencies match expected; df = k - 1 - #params estimated; EiE_{i} ≥ 5 needed
  • Same as independence
  • Requires normality

Goodness-of-fit χ2{\chi}^{2}: O vs E frequencies; adjust df for estimated params.

#hypothesis-testing#parametric-tests

Practise Statistics Fundamentals

215 interview questions in this topic.

Related questions