The first scenario to consider is when we have at hand a complete log of muzzle velocities for the entire range of air temperature, a “complete dataset.”
The second scenario, which is the more realistic, considers what happens when the data at hand is limited to a particular range of values, which is called a “limited dataset”
The performance of regression analysis methods in practice depends on the form of the data-generating process, and how it relates to the regression approach being used. Since the true form of the data-generating process is not known, regression analysis depends to some extent on making assumptions about this process.
These assumptions are sometimes (but not always) granted if a large amount of data is available. Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally.
Air temperature values are in Celsius degrees while muzzle velocity values are in feet/sec. For the “complete dataset” the air temperature scale ranges from -50°C (-58°F) to 50°C (122°F). The reason for that coverage is to handle all possible situations and to make for a real test of the fitting functions.
The “limited dataset” ranges from -15°C (-5°F) to 15°C (59°F)