Extrapolation is a statistical technique used to estimate values of data points beyond the known data set. It is a process of inferring values outside the range of the existing data to make predictions. Extrapolation attempts to predict future data by relying on historical data, such as estimating the size of a population a few years in the future on the basis of the current population size and its rate of growth. Extrapolation is an important concept in various disciplines like Mathematics, Psychology, Sociology, Statistics, etc., with some categorical data.
Extrapolation is often mistaken for interpolation, which is the act of estimating a value within two known values that exist within a sequence of values. The two use the same techniques to estimate unknown values but differ in some key areas. If the estimated values are derived within two known values, then it’s an interpolation. However, if the predicted values fall outside of the data set, then it’s extrapolation.
Common extrapolation methods include linear extrapolation and polynomial extrapolation. Linear extrapolation uses a linear equation to predict future outcomes and is best suited for predictions close to the given data. Polynomial extrapolation, on the other hand, uses a polynomial equation to make predictions about future values and is used when the data points exhibit a non-linear trend.
In summary, extrapolation is a statistical technique used to estimate values of data points beyond the known data set, and it attempts to predict future data by relying on historical data. It is an important concept in various disciplines and is often used in conjunction with interpolation.
