goodness-of-fit test

A goodness-of-fit test is a statistical hypothesis test used to determine how well an observed result conforms to a theoretical expectation or how well data fits a curve. It's a type of chi-squared test where observed frequencies are compared to expected frequencies.12

For instance, a goodness-of-fit test could assess the likelihood that a randomly selected can of soda contains a volume within an acceptable range. The test involves calculating a chi-squared value using the formula: (\chi^2 = \sum \frac{(O_i - E_i)^2}{E_i}), where (O_i) is the observed value and (E_i) is the expected value. If the calculated chi-squared value is less than a critical value from a table, the null hypothesis (that the data fits the expectation) cannot be rejected.2