There's nothing inherently wrong with a linear fit and a linear model is often more accurate than a more ostensibly correct-looking polynomial or complex functi

There's nothing inherently wrong with a linear fit and a linear model is often more accurate than a more ostensibly correct-looking polynomial or complex function which overfits the observed data. Perhaps you mean that drawing any kind of fit though this data is misleading, when lacking confidence statistics and R2 score - although you could have all those and still do poorly on held-out data, or you could even do well on held-out data and still be victim to confounders or misunderstanding the direction of causation... I see a line through data as nothing more than a hypothesis, which needs to be backed up with rigor. If it's backed up, there's nothing outrageous about it.