Interpolation is a method used to estimate or predict values within a range of known data points. Its goal is to fit a line or curve to known data points, so it is possible to estimate values where there is no exact data. For example, observe how the amount of water left in an outdoor tank changes over the course of the month. The amount of water left in the tank on the $16\text{th}$ day can be estimated from this plot. Notice that the data points follow a linear trend, so a linear model can be fitted to the data. To estimate a value for $x=16,$ find where that point would be on the line. The $y\text{-}$coordinate of this point is the estimate. The prediction indicates there were about $70$ gallons of water left in the tank on the $16\text{th}$ day of the month. Interpolation generally helps estimate unknown or unrecorded values based on existing data. These guesses are typically more accurate than those provided by extrapolation.