Interpolation is filling in the data points between the data that has already been collected. Extrapolation is filling in data points beyond the data that has already been collected, or extending the data.
Interpolation is the process of estimating the value of some data and processing it in-line with other data obtained from another source. Extrapolation is the ability to estimate the value of something outside a known range from values within that range by assuming that the unknown quantity follows logically from an analysis of the known ones
Interpolation
It's called illogical extrapolation.
Interpolation in general is a way to determine intermediate values from a set of coordinates. Linear interpolation would be to fit a single linear function to the entire set of coordinates. Piecewise linear interpolation would then be to determine intermediate values from the set of coordinates by fitting linear functions between each set of coordinates. Connect-the-dots so to speak.
Interpolation is usually found when studying two variables such that there is some mathematical relationship between them. The relationship need not be causal. Interpolation entails finding the value of one of the variables which corresponds to a given value of the other variable when that given value lies between two known values. Thus, if Y is y1 when X is x1 and Y is y2 when X is x2, interpolation is required to find the value of Y when X is between x1 and x2 or to find the value of X when Y is between y1 and y2.
Both, interpolation and extrapolation are used to predict, or estimate, the value of one variable when the value (or values) of other variable (or variables) is known. This is done by extending evaluating the underlying function. For interpolation, the point in question is within the domain of the observed values (there are observations for greater and for smaller values of the variables) wheres for extrapolation the point in question is outside the domain.
Because of what it does
Interpolation and Extrapolation
Interpolation & extrapolation
Extrapolation involves predicting values outside of the range of known data, while interpolation involves estimating values within the known data range. Extrapolation assumes that the pattern observed in existing data continues beyond what is measured, which can lead to more uncertainty compared to interpolation. Interpolation, on the other hand, is used to estimate values between existing data points.
interpolation, because we are predicting from data in the range used to create the least-squares line.
The results are more reliable for interpolation .
* plausibility * interpolation * extrapolation * 'What if?' hypothetical deviations * alternate history
Interpolation or extrapolation upon known scientific facts or principles.
Interpolation is the process of estimating the value of some data and processing it in-line with other data obtained from another source. Extrapolation is the ability to estimate the value of something outside a known range from values within that range by assuming that the unknown quantity follows logically from an analysis of the known ones
Two of the defining traits of Science Fiction are interpolation and extrapolation. Most sf is extrapolation and wild extrapolation at that and has lost much of its impact. So when some subtle interpolation comes along people (sf readers) take notice. It also touches on our own frailty as humans, giving us a new perspective on reality, something that is difficult to do in sf.
If you are predicting a point that's outside of the data range, it is known as extrapolation. If it is within the data range it is interpolation and is much more reliable.