Chi-square test

Measure of the goodness-of-fit, typically between a dataset and expected distribution. The test is applicable for both discrete and continuous data; however, for continuous data the observations must be grouped into “bins.” The frequency of occurrence of observations in each bin or classification is compared to the expected number of occurrences based on a theoretical distribution. The test statistic is expressed as:

Where observed and expected refer to a specific number of observations within each of n classes. The test statistic is compared to the chi-square distribution to determine statistical significance (Wilks 1995).

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