Interpolation and extrapolation are two methods of finding different values which come under a sequence of a straight line or in the same pattern of a curve.
Key Takeaways
- Interpolation estimates data values within a known data range using existing data points.
- Extrapolation predicts data values outside the known data range, increasing the potential for inaccuracy.
- Both methods involve estimating unknown values, but interpolation stays within the known range while extrapolation ventures beyond it.
Interpolation vs Extrapolation
Interpolation means inserting something of a different type into something else or estimating data values using existing data points that are within a known range. Extrapolation means to estimate or conclude something on the assumption that existing trends will remain applicable.
These points may be part of a straight line with an equation or a curve with constant curving. One can find values more easily and accurately through it.
Extrapolation involves finding one value based on another value, and these values lie beyond some of the data points that one already knows are accurate.
Comparison Table
| Parameters of Comparison | Interpolation | Extrapolation |
|---|---|---|
| Extension | It does not require an extension of the pattern. | It requires an extension of the pattern. |
| Finding data points | Data points are found within the range. | Data points are not found within the range. |
| Convenience | It is more convenient to find data points here. | It is less convenient to find data points here comparatively. |
| Accuracy | The data points or simple points found here are more accurate and precise compared to extrapolation. | There is more chance of finding inaccurate data points in this process compared to interpolation. |
| Easy | One can easily find data points in this process. | One cannot easily find data points in this process. |
What is Interpolation?
Interpolation is the process of finding values that fall under a particular range of values. Interpolation helps to find data that is part of a data range.
Hence, only a few points of a particular location are taken as a reference point so that the rest are determined based on the constant pattern with the help of interpolation.
When two points are connected to each other on a plane surface, an equation can be found for the line based on the two points of reference.
There are various other points that are connected on the ways of connecting these two points, and these can be taken as the points that are found using the interpolation process.
What is Extrapolation?
Extrapolation can be a little more complicated compared to interpolation. Similar to interpolation, it requires one to find points, but this time, the points do not lie in between the data points we already have.
If the extension of the graph pattern is not possible, one has to find an estimated point according to the pattern.
One example of this is a plane connecting two points. When we join them with the help of a line, the line incorporates an infinite number of points in it.
These points can be easily located if the line is further extended, but this is not always possible, similar to the case of finding whether points of a location.
Main Differences Between Interpolation and Extrapolation
- Interpolation has values within the range, whereas extrapolation does not.
- Interpolation requires less time than extrapolation.
Last Updated : 06 September, 2023
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Piyush Yadav has spent the past 25 years working as a physicist in the local community. He is a physicist passionate about making science more accessible to our readers. He holds a BSc in Natural Sciences and Post Graduate Diploma in Environmental Science. You can read more about him on his bio page.
While the content is quite informative, it seems to lack a compelling argument for the relevance of these methods in real-world applications.
Extrapolation is definitely underappreciated. It plays a crucial role in making predictions that go beyond existing data and provides valuable insights into future trends and patterns.
I understand your perspective, but we must also emphasize the potential inaccuracies that come with extrapolating beyond the known data range.
The article presents a well-structured overview of interpolation and extrapolation with insightful examples. It has provided a comprehensive understanding of the topic.
Absolutely, the article’s clarity and coherence make it an invaluable resource for both students and professionals.
Agreed. I found the section on ‘What is Extrapolation?’ very thought-provoking and enlightening.
The comparison table offers a clear and concise summary of the differences between interpolation and extrapolation. It effectively highlights the advantages and disadvantages of each method.
A very well written explanation of interpolation and extrapolation. It is very informative and accurate. The explanation is detailed and serves as a great resource for easy understanding.
I completely agree. The article does a great job at explaining the difference between the two methods with excellent examples.
This reads like a comedy skit on mathematical concepts! Who knew numerical methods could be so entertaining?
I agree, the author’s approach to explaining technical concepts keeps the readers engaged and entertained.
Exactly! The author’s witty tone makes a complex topic accessible and enjoyable to read.
I find the inclusion of references to scholarly articles and research publications particularly commendable. It adds credibility and depth to the discussion of interpolation and extrapolation.
This is a bit too detailed. A simpler explanation could make it more accessible to a wider audience.