Abstract
The paper questions the use of the Pearson chi-square goodness-of-fit test for discrete models in linguistics. It is argued that the stochastic independence, one of necessary conditions for a correct application of the test, is not realistic for linguistic data. Several alternative possibilities (computational and empirical approaches) are suggested. Advantages and drawbacks of the alternatives are discussed.
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