Simplest Interpolating Polynomial

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In summary, the task is to find the simplest interpolating polynomial that can predict the constant-pressure specific heat within 1% error over a given range of temperatures. This involves using methods such as general least squares, polynomial regression, linear regression, Newton's interpolating polynomials, and Lagrange interpolating polynomials, but since the problem specifically mentions interpolating polynomials, the simplest fifth degree polynomial should suffice.
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chronicals
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Homework Statement


Consider the data in the following table for constant-pressure specific heat, C
p (kJ/kg.K) at various temperatures T (K). Determine the simplest interpolating polynomial that is likely to predict Cp within 1% error over the specified range of temperature.

T : 1000 1100 1200 1300 1400 1500
Cp 1.410 1.1573 1.1722 1.1858 1.1982 1.2095




Homework Equations





The Attempt at a Solution


I am very confused, i am studying ''general least squares,polynomial regression, linear regression, Newton's interpolating polynomials, lagrange interpolating polynomials'' now. I have a question but i don't know which method i should use, can you help me quickly? Thanks. This is my question:
 
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  • #2
Since the problem says "interpolating polynomials", that let's out any least squares or regression- and, here, both Newton's and Lagrange's methods should give the same fifth degree polynomial.
 

1. What is the Simplest Interpolating Polynomial?

The Simplest Interpolating Polynomial is the polynomial of the lowest degree that passes through a given set of points. It is used in polynomial interpolation, a method of finding a polynomial function that fits a given set of data points.

2. How is the Simplest Interpolating Polynomial calculated?

The Simplest Interpolating Polynomial is calculated using the Lagrange interpolation formula. This formula takes into account the coordinates of the given points and calculates the coefficients of the polynomial function that passes through them.

3. What is the degree of the Simplest Interpolating Polynomial?

The degree of the Simplest Interpolating Polynomial is equal to the number of data points minus one. For example, if there are five data points, the Simplest Interpolating Polynomial will be a fourth-degree polynomial.

4. What are the limitations of the Simplest Interpolating Polynomial?

The Simplest Interpolating Polynomial can only accurately fit a set of data points if the points are evenly spaced and there are no outliers. It may also produce a large error if the data points are spread out over a large range.

5. How is the Simplest Interpolating Polynomial used in real-world applications?

The Simplest Interpolating Polynomial has many practical applications in fields such as engineering, science, and data analysis. It can be used to predict values between known data points, create smooth curves from scattered data, and approximate unknown functions based on limited data points.

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