6. If the model is bad (fails to predict outcomes better than a constant, and/or predicts very little of the variation in the data) we should not look at the regression coefficients. In this case, there would be no evidence that any of the coefficients have other than a zero value. From questions 4 and 5, above, what can you conclude about the suitability of the data for continuing on and looking at the regression coefficients? Is it worth bothering to even look at the coefficients for Model 5's two analyses (one of the US/China dataset, and the other of the Finland dataset)