(Solution) - In a study of the causes of bearing wear a -(2025 Original AI-Free Solution)

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In a study of the causes of bearing wear, a machine was run 24 times, with various loads (denoted x1), oil viscosities (x2), and ambient temperatures (x3). The wear, denoted y, was modeled as y = ?0 + ?1x1 + ?2x2 + ?3x3 + ?4x1x2 + ?5x1x3 + ?6x2x3 + ?. When this model was fit to the data, the sum of squares for error was SSE = 9.37. Then the reduced model y = ?0 + ?1x1 + ?2x2 + ?3x3 was fit, and the sum of squares for error was SSE = 27.49. Is it reasonable to use the reduced model, rather than the model containing all the interactions, to predict wear? Explain.