3NMNLA(4): Numerical Methods & Numerical Linear Algebra Semester 2 (Spring 2023)
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Semester 2 (Spring 2023)
3NMNLA(4): Numerical Methods & Numerical Linear Algebra
Section: Numerical Methods
Assessed Problem Sheet 2
This problem sheet is part of continuous assessment in this module. Your solu- tions to all problems in this assignment will be assessed. The marks are indicated in square brackets next to each problem.
Assignment available from: 15 March 2023.
Submission due: 17.00 on 28 April 2023.
Feedback opportunities pre-submission:
● Guided study sessions – discussion with module lecturer and PGTAs
● Lecturer’s office hours on Wednesdays at 11.00am– 12.30pm
Feedback opportunities post-submission:
● Marked submission
● Model solutions
● Generic feedback (released in week 12)
● Lecturer’s office hours on Wednesdays at 11.00am– 12.30pm
Submission: your complete written solutions to all four problems below should be scanned or photographed and uploaded on CANVAS as a pdf-file. LATEX typeset solutions will be accepted as well. All work submitted must be your own.
1. Let the function f (x) be given by its values at four points as follows: f ( ·2) = 1, f (0) = · 1, f (1) = 10, f (3) = 4.
Using the method of normal equations, find the least-squares approximation of these data by a linear polynomial. [7]
4
2. (i) Write Simpson’s rule for approximate calculation of the integral f (x) dx and −2
state its degree of exactness. [3] (ii) If a Gaussian quadrature formula has the degree of exactness equal to 7, how many nodes this formula is based on? [2]
3. Derive an interpolatory quadrature with the nodes x0 = 0, x1 = 1, x2 = 3 for approx- imating the integral
0
f (x) dx.
− 1
[8]
4. Design the composite Gaussian quadrature for approximating the integral
1
f (x) dx.
0
The quadrature must satisfy the following requirements:
– it is based on the partition of the interval (0, 1) into K 2 1 subintervals of equal size;
– the degree of exactness is equal to 3;
– it is written in terms of K and f only. [10]
2023-04-20