Linear & Polynomial
Support for both linear and polynomial interpolation methods with Newton's divided differences algorithm.
Professional Interpolation Calculator
Calculate missing data points with precision using linear interpolation and polynomial interpolation methods. Perfect for curve fitting, data estimation, and numerical analysis.
Interpolation Method
Data Points
Enter your known (x, y) coordinate pairs:
Calculate Value At
Results
Enter data points and click Calculate to see results
Why Choose Our Interpolation Tool?
Real-time Results
Instant calculations without page reloads. See results as you type your data points.
Mobile-First Design
Optimized for all devices with responsive design and touch-friendly interface.
API Access
RESTful API for developers to integrate interpolation calculations into their applications.
CSV Export
Download your interpolation results as CSV files for further analysis in Excel or other tools.
Secure & Private
All calculations performed client-side. Your data never leaves your browser.
Common Applications
Scientific Research
Estimate missing experimental data points in research studies and laboratory analysis.
Engineering
Calculate intermediate values in engineering calculations and design specifications.
Financial Analysis
Interpolate financial data for trend analysis and forecasting models.
Data Science
Fill gaps in datasets using mathematical interpolation for machine learning preprocessing.
Frequently Asked Questions
What is interpolation used for?
Interpolation is used to estimate unknown values between known data points. It's essential in numerical methods, scientific computing, and data analysis for filling gaps in datasets and creating smooth curves through discrete points.
What's the difference between linear and polynomial interpolation?
Linear interpolation connects data points with straight lines, while polynomial interpolation uses higher-degree polynomials to create smoother curves. Polynomial methods like Newton's divided differences can capture more complex relationships in your data.
How accurate are the calculations?
Our calculator uses double-precision floating-point arithmetic for maximum accuracy. The precision depends on your input data quality and the chosen interpolation method.
Can I use this for regression analysis?
While interpolation and regression analysis are related, they serve different purposes. Interpolation passes exactly through your data points, while regression finds the best-fit line or curve that may not pass through all points.