The error term can be thought of as the composite of a number of minor influences on the target variable that cannot be captured by the model. As the number of these minor influences gets larger, the distribution of the error term tends to approach the normal distribution. This tendency is called the Central Limit Theorem. The t-test and F-test are not applicable unless the error term is normally distributed.

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