Final answer:
After comparing a theory to real-world data, there are three possible outcomes: if the theory fits poorly, it is best to move on to a new research question; if the theory fits well, it can be used to make predictions; and there is no reason to settle for a theory that only somewhat fits the data.
Step-by-step explanation:
After a theory has been compared to real-world data, there are several possible outcomes:
A) If the theory fits poorly with real-world data, it is best to move on to an entirely new research question before attempting to revise the failed theory. This is because a theory that does not align with the data is likely to be inaccurate and may not provide meaningful insights.
B) If the theory fits well with the data, you can use that theory to make predictions. When a theory accurately explains and predicts real-world observations, it increases our confidence in its validity and usefulness.
C) There is never a reason to make do with a theory that fits only somewhat well with real-world data. It is important for theories to be consistent with available data and other current theories. If a theory only partially fits with the data, it may indicate that there are still gaps or limitations in our understanding, and further investigation or refinement is necessary.