Final answer:
The best example of an alternate hypothesis in multiple regression is to state that at least one predictor has a nonzero effect, which contrasts with the null hypothesis that all coefficients are zero.
Step-by-step explanation:
The best example of an alternate hypothesis for a global test of a multiple regression model might be to state that at least one of the predictors has a nonzero coefficient. This contrasts with the null hypothesis, which typically posits that all coefficients in the model are zero (meaning that none of the predictors have an effect).
For example, if we are testing a multiple regression model with predictors A, B, and C, the alternative hypothesis could be stated as: 'At least one of A, B, or C has a nonzero coefficient in the model.' This indicates that we are looking for evidence that at least one of these factors has an impact on the response variable.
In the context of the provided information, instead of testing a single null hypothesis, utilizing multiple working hypotheses allows us to consider multiple possible models or explanations simultaneously, thereby acknowledging the complexity of the system under study and potentially providing a more nuanced understanding of the system's behavior.