CSIT 3rd Semester
Numerical Method Board Question Paper 2082 Old Course


CSC 212-2082 ✡
Tribhuvan University
Institute of Science and Technology
2082
Bachelor Level/Second Year/Third Semester/Science
Computer Science Information Technology (CSC 212)
(Numerical Method)
(Old Course)
Full Marks:60 Pass Marks:24 Time:3 hours

Candidates are required to give their answers in their own words as for as practicable.
The figures in the margin indicate full marks

Section A
Long Answer Questions
Attempt any Two question.
[2x10=20]
1.

Explain different types of numerical errors with example. Find the root of the equation f(x) = x3 + 3x + 1 in the using Newton Raphson Method using initial value x₀ = 3 .

2.

What is interpolation? Find the functional value at x = 0.5 from the following data using forward difference formula.

X00.20.40.60.8
f(x)00.240.550.921.63

3.

Evaluate ∫₁² ex² dx using Simpson's rule with n=6. Also evaluate the same integral using Gaussian 3 -point formula and compare the result.

Section B

Attempt any Eight questions

[8x5=40]
4.

Solve the system of linear equation using Gauss elimination method.
3x + 6y + z = 16
2x + 4y + 3z = 13
x + 3y + 3z = 9

5.

Solve the following differential equation dy/dx = 3x + y/2 with y(0) = 1 for x = 0.2 (h = 0.1) using Euler's Method.

6.

Solve the Poisson's equation ∇²f = 2x²y² over the square domain 0≤ x ≤ 3 and 0 ≤ y ≤ 3 with f = 0 on the boundary and h=1.

7.

What is initial value problem? Use RK fourth order method to estimate y(0.4) of the equation dy/dx = x² + y² with y(0)=0 (assume h=0.2).

8.

Calculate the integral value of∫₀² 1/(x+4) dx by using Simpson's 3/8 rule with 9 segments.

9.

Find the root of eˣ − 3x = 0, using bisection method correct to two decimal places.

10.

Apply Gauss-Jordan elimination method to solve the following system of equations:
x + y + z = 9
2x-3y+4z=13
3x+4y+5z=40

11.

Fit a second degree polynomial y=a+bx+cx² to the data (1, 1.1), (1.5, 1.3), (2.0, 1.6), (2.5, 2.0), (3.0, 2.7), (3.5, 3.4) and (4, 4.1).

12.

Explain about least square linear regression and describe its application.