Skip to content

Goodness of Fit

Chi-Square Distributions

A continuous probability distribution of the sum of the squares of kk independent variables

Each of these independent variables follows a standard normal distribution

  • Positively skewed
  • Non-negative
  • dof = k1k-1
  • \uparrow dof     \implies chi-square distribution closer to normal distribution

When Is Chi-Square Distribution Used

  • Goodness of fit tests
  • Tests of independence
  • Tests of homogeneity

Hypothesis Tests for Goodness of Fit

A measure of how well real-life observed data fits a theoretical model

Calculate Chi-Square Value

χ2=(observedexpected)2expected\chi^2 = \sum \dfrac{(observed - expected)^2}{expected}

Conclude A Hypothesis Test

  • χ2>critical value    \chi^2 > critical\ value \implies reject H0H_0
  • χ2<critical value    \chi^2 < critical\ value \implies not reject H0H_0