In modules 2 and 3, we created scatter plots with trend lines in Tableau, and we were able to assess if the "model fits the data" based on how closely the trend line matched the general pattern of the dots in the scatter plot. Why did we need to learn more complicated methods to assess model accuracy in this module? *Recall that a model "fits the data" when the model's trend line follows the same general pattern/trend in the data. Question 5 options: The accuracy plots we learned in this module was extra information that are not necessary in assessing if a model fits the data. For any type of model, we can determine if the model fits the data based on the p-values of the model. The accuracy plots we learned in this module was extra information that are not necessary in assessing if a model fits the data. For any type of model, we can determine if the model fits the data based on the R-squared of the model. Because the graphical methods in Module 2 and 3 only work when we have one quantitative x-variable; the plots we learned in this module can be used to assess