what is interpolation versus extrapolation
Interpolation and extrapolation are both methods used in statistics and data analysis to estimate values based on existing data points.
Interpolation is the process of estimating values within the range of known data points. It involves predicting values that fall between two known data points using mathematical techniques such as linear interpolation, polynomial interpolation, or spline interpolation.
Extrapolation, on the other hand, is the process of estimating values outside the range of known data points. It involves extending the known data points to make predictions about values beyond the observed data. Extrapolation is often less reliable than interpolation, as it involves making assumptions about the trend or pattern of the data beyond what is observed.
In summary, interpolation is used to estimate values within a known range of data, while extrapolation is used to estimate values outside that range. Both techniques have their uses in statistics and data analysis, but it is important to be cautious and mindful of the limitations and potential errors associated with extrapolation.