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Realistic data contains very complicated relationships that are non-linear. In statistics, nonlinearity is a relationship between a variable that cannot be described by a line. Therefore, to understand the non-linear relationships in the data, a more sophisticated model architecture such as neural networks must be used. Simple methods such as linear regression would not be able to capture all the complex patterns that are present in real data.