The interaction of all three—the affect of each on the other—is more important than any parameter individually (i.e. the sum is greater than the parts). Therefore just knowing 2 parameters is a very different level of knowledge than knowing all three. In addition, calibration of three parameters separately leads to variability in data collection methods making this information less representative of key decision making factors over time.
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