Problem 1

1.1 Problem definition

1.2 Solution of the problem

1.2.1 Linear interpolation

1.2.2 Method of least squares interpolation

1.2.3 Lagrange interpolating polynomial

1.2.4 Cubic spline interpolation

1.3 Results and discussion

1.3.1 Lagrange polynomial

Problem 2

2.1 Problem definition

2.2 Problem solution

2.2.1 Rectangular method

2.2.2 Trapezoidal rule

2.2.3 Simpson's rule

2.2.4 Gauss-Legendre method and Gauss-Chebyshev method

Problem 3

3.1 Problem definition

3.2 Problem solution

Problem 4

4.1 Problem definition

4.2 Problem solution

References

Problem 1

1.1 Problem definition

For the following data set, please discuss the possibility of obtaining a reasonable interpolated value at , , and via at least 4 different interpolation formulas you are have learned in this semester.

1.2 Solution of the problem

Interpolation is a method of constructing new data points within the range of a discrete set of known data points.

In engineering and science one often has a number of data points, as obtained by sampling or experimentation, and tries to construct a function which closely fits those data points. This is called curve fitting or regression analysis. Interpolation is a specific case of curve fitting, in which the function must go exactly through the data points.

First we have to plot data points, such plot provides better picture for analysis than data arrays

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