Extrapolate vs. Interpolate

What are the differences between extrapolate and interpolate?

Extrapolate is the process of extending a known set of data points beyond the range of the data set. For example, if you have a set of data points that range from 0 to 10, you could extrapolate beyond 10 to estimate the value of 11. Interpolate is the process of estimating the value of a data point that lies between two known points. For example, if you have a set of data points that range from 0 to 10, you could interpolate the value of 5.5 by estimating the value of the data point that falls between 5 and 6.

Why do people commonly confuse extrapolate and interpolate?

People commonly confuse extrapolate and interpolate because the two terms are similar in nature. Both extrapolate and interpolate involve extrapolating or predicting data points outside of the given data set, but they differ in the type of data they use. Extrapolation uses data at the extremes of a data set to predict outside of the data set, while interpolation uses data within the data set to make predictions. Due to the similarity between the two terms, people often confuse them.

What are some ways to make sure you don't confuse extrapolate and interpolate?

Understand the definitions of each word. Extrapolate means to estimate something beyond the available data, while interpolate means to estimate something by using the available data.
Choose the right verb to use. If you are estimating something beyond available data, use the verb “extrapolate.” If you are estimating something by using the available data, use the verb “interpolate.”
Create a visual reminder. Make a chart or write a few sentences that clearly explain the difference between extrapolate and interpolate.
Use context clues. Read the sentence and ask yourself if the data you are estimating is from the given information or from outside sources.
Read your sentences aloud. As you read your sentence out loud, ask yourself if you are extrapolating or interpolating the data.

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