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One assumption underlying linear regression is that the x values are normally distributed.

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The answer is true. The linear regression analysis necessitates all variables to be multivariate normal. This supposition can best be checked with a histogram. Normality can be checked with a goodness of fit test. When the data is not normally distributed a non-linear transformation can answer this issue.

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