The log-likelihood statistic is analogous to the residual sum of squares in multiple regression in the sense that it is an indicator of how much unexplained information there is after the model has been fitted. It, therefore, follows that values of the log-likelihood statistic indicate poorly fitting statistical models.

A. small

Step-by-step explanation:

According to a different source, these are the options that come with this question:

A. small

B. large

The log-likelihood statistic is an indicator of how much explained information there is after the model has been fitted. This means that the higher the log-likelihood, the better our model fits the available data. In other words, it also means that the small values of the log-likelihood statistic indicate poorly fitting statistical models.

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step-by-step explanation:

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