01
Floating-point error
Choose a computational method, track approximation error and stability, and compare the output with a known bound or independent estimate.
Goal: recognise a floating-point error problem from its wording, carry out the governing method, and check that the result is reasonable.
02
Root finding
Define the central objects, connect at least two representations, solve direct and unfamiliar applications, and explain how the result can be checked.
Goal: recognise a root finding problem from its wording, carry out the governing method, and check that the result is reasonable.
03
Interpolation
Choose a computational method, track approximation error and stability, and compare the output with a known bound or independent estimate.
Goal: recognise a interpolation problem from its wording, carry out the governing method, and check that the result is reasonable.
04
Numerical differentiation
Relate local change to slope, apply the appropriate derivative rule, and use sign, units, and graph behavior to interpret the result.
Goal: recognise a numerical differentiation problem from its wording, carry out the governing method, and check that the result is reasonable.
05
Numerical integration
Represent accumulated change, choose bounds and technique carefully, and check the result with units, area, or differentiation.
Goal: recognise a numerical integration problem from its wording, carry out the governing method, and check that the result is reasonable.
06
Linear systems
Represent the constraints symbolically, choose an equivalence-preserving solution method, and verify the result in every original relationship.
Goal: recognise a linear systems problem from its wording, carry out the governing method, and check that the result is reasonable.
07
ODE solvers
Define the central objects, connect at least two representations, solve direct and unfamiliar applications, and explain how the result can be checked.
Goal: recognise a ode solvers problem from its wording, carry out the governing method, and check that the result is reasonable.
Numerical Methods questions with worked answers
These 8 questions are printed in full on this page and are drawn across all 7 course units. Nothing here is generated on the fly. Cover the options, solve each one on paper, and only then open the worked answer to compare your method with the one shown.
Question 1: The value 2.71828 is approximated by 2.72. What are the absolute and relative errors?
Numerical Methods · Floating-point error
- absolute 0.00172, relative about 0.063%
- absolute 0.00172, relative about 0.63%
- absolute 0.0172, relative about 0.063%
- absolute 0.172, relative about 6.3%
Show the worked answer
- Absolute error is the size of the difference: |2.72 - 2.71828| = 0.00172.
- Relative error divides that by the true value.
- 0.00172 / 2.71828 = 0.000633.
- As a percentage that is about 0.063%.
Answer: absolute 0.00172, relative about 0.063%
Question 2: Bisection is applied to f(x) = x^3 - x - 2 on [1, 2]. What is the interval after the first step?
Numerical Methods · Root finding
- [1.5, 2]
- [1, 1.5]
- [1.25, 1.75]
- [1.5, 1.75]
Show the worked answer
- Check the ends: f(1) = -2 and f(2) = 4, so a root lies between them.
- The midpoint is 1.5, and f(1.5) = 3.375 - 1.5 - 2 = -0.125.
- f(1.5) is negative, the same sign as f(1), so the root is not in the left half.
- Keep the half where the sign changes: [1.5, 2].
Answer: [1.5, 2]
Question 3: Apply one Newton step to f(x) = x^2 - 10 starting at x0 = 3. What is x1, to five decimal places?
Numerical Methods · Root finding
- 3.16667
- 3.16228
- 3.33333
- 3.15000
Show the worked answer
- Newton's rule is x1 = x0 - f(x0) / f'(x0).
- f(3) = 9 - 10 = -1 and f'(x) = 2x, so f'(3) = 6.
- x1 = 3 - (-1 / 6) = 3 + 0.166667.
- x1 = 3.16667, already close to the true root 3.16228.
Answer: 3.16667
Question 4: Linear interpolation uses the points (2, 5) and (6, 17). What value does it predict at x = 3.5?
Numerical Methods · Interpolation
- 9.5
- 11.0
- 8.0
- 10.25
Show the worked answer
- The slope between the points is (17 - 5) / (6 - 2) = 12 / 4 = 3.
- From x = 2 to x = 3.5 is a step of 1.5.
- The rise over that step is 3 x 1.5 = 4.5.
- 5 + 4.5 = 9.5.
Answer: 9.5
Question 5: Use the central difference with h = 0.1 to estimate the derivative of f(x) = x^3 at x = 2.
Numerical Methods · Numerical differentiation
- 12.01
- 12.00
- 12.61
- 11.41
Show the worked answer
- The central difference is [f(x + h) - f(x - h)] / (2h).
- 2.1^3 = 9.261 and 1.9^3 = 6.859.
- The difference is 9.261 - 6.859 = 2.402, and 2h = 0.2.
- 2.402 / 0.2 = 12.01. The exact derivative is 12, so the error is 0.01.
Answer: 12.01
Question 6: Use the trapezoid rule with 4 equal strips to estimate the integral of x^2 from 0 to 2.
Numerical Methods · Numerical integration
- 2.75
- 2.67
- 2.50
- 3.00
Show the worked answer
- With 4 strips the width is h = 0.5 and the x values are 0, 0.5, 1, 1.5, 2.
- The heights are 0, 0.25, 1, 2.25, and 4.
- The rule is (h/2) times [first + last + 2 x (all the middle heights)]: the middle heights add to 3.5, doubled to 7.
- (0.5 / 2)(0 + 4 + 7) = 0.25 x 11 = 2.75. The exact value is 2.667, so the estimate is a little high.
Answer: 2.75
Question 7: Apply one Gauss-Seidel sweep to 4x + y = 9 and x + 3y = 8, starting from x = 0 and y = 0.
Numerical Methods · Linear systems
- x = 2.25, y = 1.9167
- x = 2.25, y = 2.6667
- x = 2.0, y = 2.0
- x = 1.9167, y = 2.25
Show the worked answer
- Solve the first equation for x: x = (9 - y) / 4. With y = 0 that gives x = 2.25.
- Gauss-Seidel uses the new x straight away.
- Solve the second equation for y: y = (8 - x) / 3 = (8 - 2.25) / 3.
- 5.75 / 3 = 1.9167. The exact solution is x = 19/11 = 1.7273 and y = 23/11 = 2.0909, so more sweeps are needed.
Answer: x = 2.25, y = 1.9167
Question 8: Use Euler's method with h = 0.5 on y' = y, y(0) = 1, for two steps. What is the estimate of y(1)?
Numerical Methods · ODE solvers
- 2.25
- 2.72
- 2.00
- 1.50
Show the worked answer
- Euler's rule is new y = old y + h times the slope, and here the slope is y itself.
- Step one: y = 1 + 0.5(1) = 1.5.
- Step two: y = 1.5 + 0.5(1.5) = 2.25.
- The true value is e = 2.718, so Euler's method with this step size falls short.
Answer: 2.25
Which unit each printed question belongs to
Use this map after marking your work. If two misses share a unit, review that unit before starting a generated set.
How the generated Numerical Methods sets are created
The 8 questions above are fixed and checked. The generator at the top of the page is different: it writes fresh questions with AI from the course and unit information shown here, then the application checks each one for a complete prompt, four choices, one keyed answer, and an explanation. Generated questions are original practice—not official or released exam questions—and AI can still make mathematical mistakes. Verify a disputed answer with the stated method, your course materials, or the MathGPT solver, and follow the site's academic-integrity guidance.
Questions about this Numerical Methods practice page
What does this page cover?
It covers all 7 Numerical Methods units listed above. Choose one unit for focused work, or mixed review to test method selection, and switch to test mode when you want all units mixed under time.
When can I see correct answers and explanations?
The 8 printed questions on this page keep their worked answers behind a toggle, so you can check any one of them straight away. In the generator above, practice mode explains each question as soon as you answer it, while test mode holds every explanation until you submit.
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