Numerical Methods: cram pack

Formula sheets, the key method steps for every topic and 8 practice problems, with full solutions at the back.

New problemsBack to the course

In the print window, choose “Save as PDF” to keep a copy on your device.

1Formulas and methods

Numerical methods

Bisection
c = (a + b)/2, width after n steps (b − a)/2ⁿ
Newton–Raphson
xn+1 = xₙ − f(xₙ)/f′(xₙ)
Linear interpolation
y = y₁ + (y₂ − y₁)(x − x₁)/(x₂ − x₁)
Trapezoid rule
T = (h/2)[f₀ + 2f₁ + … + 2fn−1 + fₙ], h = (b − a)/n
Simpson’s rule (n even)
S = (h/3)[f₀ + 4f₁ + 2f₂ + … + 4fn−1 + fₙ]
Trapezoid error bound
|E| ≤ (b − a)h²M/12, M = max|f″|
Euler
yn+1 = yₙ + h·f(tₙ, yₙ)
Heun
yn+1 = yₙ + (h/2)(k₁ + k₂), k₂ = f(tₙ + h, yₙ + hk₁)
RK4
yn+1 = yₙ + (h/6)(k₁ + 2k₂ + 2k₃ + k₄)

Method

  1. For a root: check the sign change for bisection, or compute f and f′ for Newton, and keep six or more digits in a table of iterates.
  2. For a table value: interpolate linearly between the two neighbouring points.
  3. For an integral: find h = (b − a)/n, list f at every node, apply the weights (1, 2, …, 2, 1 for trapezoid; 1, 4, 2, …, 4, 1 for Simpson with even n) and multiply by h/2 or h/3.
  4. For an ODE: step from t₀ with yₙ₊₁ = yₙ + h·f(tₙ, yₙ) (Euler) or the averaged slope (Heun), one row per step, until you reach the requested t.

Sequences & series

Arithmetic sequence
aₙ = a₁ + (n − 1)d, Sₙ = n(a₁ + aₙ)/2
Geometric sequence
aₙ = a₁rⁿ⁻¹, Sₙ = a₁(1 − rⁿ)/(1 − r)
Infinite geometric series
S = a₁/(1 − r), |r| < 1
p-series
Σ1/kᵖ converges only for p > 1
Ratio test
L = lim |ak+1/ak|: L < 1 converges, L > 1 diverges
Radius of convergence
R = lim |ck/ck+1|
Taylor polynomial
Pₙ(x) = Σ f⁽ᵏ⁾(a)(x − a)ᵏ/k!
Maclaurin series
eˣ = Σxᵏ/k!, sin x = x − x³/3! + …, cos x = 1 − x²/2! + …, ln(1 + x) = x − x²/2 + …
Lagrange error bound
|Rₙ| ≤ M·|x − a|ⁿ⁺¹/(n + 1)!

Method

  1. Identify the type: arithmetic (constant difference), geometric (constant ratio), a standard series, a power series or a Taylor polynomial.
  2. For sums use Sₙ = n(a₁ + aₙ)/2, Sₙ = a₁(1 − rⁿ)/(1 − r), or S = a₁/(1 − r) when |r| < 1, with a₁ the first term of the sum.
  3. For convergence: n-th term test first, then compare with Σ1/kᵖ or a geometric series, and use the ratio or root test for factorials and k-th powers.
  4. For Taylor polynomials list f(a), f′(a), f″(a), …, divide the k-th derivative by k!, and bound the error with M·|x − a|ⁿ⁺¹/(n + 1)!.

Matrices & determinants

2×2 determinant
det = ad − bc
2×2 inverse
A⁻¹ = (1/det)·[d −b; −c a]
Product
(AB)ij = Σk AikBkj
Eigenvalues
det(A − λI) = 0
Cramer’s rule
xi = det(Ai)/det(A)

Differential equations

Exponential growth/decay
dy/dt = ky → y = y0ekt
Half-life
k = ln 2 / t½
Newton's law of cooling
T(t) = Ta + (T0 − Ta)e−kt
Integrating factor
y′ + p(x)y = q(x): μ = e∫p dx, (μy)′ = μq
Mixing tank
dm/dt = r·c − (r/V)·m

2Practice problems

1.Numerical methodsMedium
xy00.511.52

Approximate ∫02 e−x² dx with the trapezoid rule using n = 4 strips. Give T.

f(x) = e−x²[a, b] = [0, 2]n = 4
T =
2.Numerical methodsHard
00.20.40.6−1−0.8−0.6ty(0, −1)

Use Euler's method with h = 0.25 for y′ = −2ty, y(0) = −1 to estimate y3 ≈ y(0.75).

y′ = −2tyy(0) = −1h = 0.25
y3 =
3.Sequences & seriesMedium
xx₀ = 2??R

The power series Σk=1∞ k!·(x − 2)ᵏ/kᵏ converges on an interval around x₀ = 2. Find the left end x of that interval.

Σ k!·(x − 2)ᵏ/kᵏx₀ = 2
x =
4.Sequences & seriesHard

f(x) = sin x is approximated by its Maclaurin polynomial of degree 5 at x = 0.3. Use the Lagrange error bound M·|x|ⁿ⁺¹/(n + 1)! with M = 1 to find the largest possible error |R₅|.

f(x) = sin xn = 5x = 0.3M = 1
|R₅| =
5.Matrices & determinantsMedium
A =2−22−1−400−32

Find the determinant det A of the 3×3 matrix A shown.

A = [2 −2 2; −1 −4 0; 0 −3 2]
det A =
6.Matrices & determinantsHard
A =−25−43b =7−11

Solve the system −2x + 5y = 7 and −4x + 3y = −11. Find x.

−2x + 5y = 7−4x + 3y = −11
x =
7.Differential equationsMedium
t (min)T (°C)6Ta​10 °C7 °C

A can of soda at 5 °C is taken out of the fridge into a room at 29 °C. After 6 min its temperature is 10 °C. It follows Newton's law of cooling, dT/dt = −k·(T − Tₐ). How long after the start, t, does it take to reach 7 °C?

T0 = 5 °CTa = 29 °CT(6) = 10 °CT = 7 °C
t = min
8.Differential equationsHard
tyK = 2ymax​ = ?

A system obeys y″ + 3y′ + 6.25y = 12.5 for t ≥ 0, starting from rest: y(0) = 0, y′(0) = 0. Find the peak value ymax of its step response.

y″ + 3y′ + 6.25y = 12.5y(0) = 0y′(0) = 0
ymax =

3Solutions

1.Numerical methods

Answer: T = 0.8806

Numerical integration: split [a, b] into n strips of width h = (b − a)/n with nodes x₀ … xₙ. Trapezoid rule: T = (h/2)[f₀ + 2f₁ + 2f₂ + … + 2fn−1 + fₙ]. Simpson's rule (n even): S = (h/3)[f₀ + 4f₁ + 2f₂ + 4f₃ + … + 4fn−1 + fₙ]. The trapezoid error shrinks like h² (bound (b − a)h²·M/12 with M = max|f″|), Simpson's like h⁴, so Simpson is usually far more accurate for the same nodes.

ixᵢf(xᵢ)weight001110.50.7788012210.367879231.50.1053992420.01831561

Nodes and values

h = 0.5
Σ wᵢfᵢ = 1 + 2·0.778801 + 2·0.367879 + 2·0.105399 + 0.0183156 = 3.522475

Trapezoid rule

T = (0.5/2)·3.522475 = 0.8806

Answer

T = 0.8806

This integral has no elementary antiderivative, which is exactly when a numerical rule is needed.

2.Numerical methods

Answer: y3 = −0.6563

Numerical solution of y′ = f(t, y): Euler's method steps along the slope at the start of each step: yn+1 = yₙ + h·f(tₙ, yₙ). Heun's method (improved Euler) averages the slope at the start and at an Euler prediction: k₁ = f(tₙ, yₙ), k₂ = f(tₙ + h, yₙ + h·k₁), yn+1 = yₙ + (h/2)(k₁ + k₂). The classical Runge–Kutta method (RK4) combines four slopes: yn+1 = yₙ + (h/6)(k₁ + 2k₂ + 2k₃ + k₄). The global error of Euler is proportional to h, Heun's to h², RK4's to h⁴.

ntₙyₙf(tₙ, yₙ)yₙ₊₁00−10−110.25−10.5−0.87520.5−0.8750.875−0.65625

Euler steps

y₁ = −1 + 0.25·(0) = −1
y₂ = −1 + 0.25·(0.5) = −0.875
y₃ = −0.875 + 0.25·(0.875) = −0.65625
00.20.40.6−1−0.8−0.6ty

Graph

y3 = −0.6563

Answer

y3 = −0.6563

The exact value is y(0.75) = −0.569783.

3.Sequences & series

Answer: x = −0.7183

Convergence: if the terms do not tend to 0 the series diverges (n-th term test). Σ1/kᵖ converges only for p > 1, and Σrᵏ only for |r| < 1. Compare a series with one of these when its terms behave like them for large k. Ratio test: L = lim |ak+1/ak|; root test: L = lim |ak|1/k. L < 1 converges, L > 1 diverges, L = 1 decides nothing. A power series Σck(x − x₀)ᵏ converges for |x − x₀| < R with R = lim |ck/ck+1|; an alternating series with terms decreasing to 0 converges.

Coefficients

ck/ck+1 = (1 + 1/k)ᵏ → e

Radius

R = 2.718

Interval

−0.7183 < x < 4.718
x = −0.7183

Answer

x = −0.7183

The ratio test says nothing at the two end points; they have to be checked separately.

4.Sequences & series

Answer: |R₅| = 1.012 × 10⁻⁶

Taylor polynomials: near x = a a smooth function is approximated by Pₙ(x) = f(a) + f′(a)(x − a) + f″(a)(x − a)²/2! + … + f⁽ⁿ⁾(a)(x − a)ⁿ/n!; for a = 0 this is the Maclaurin polynomial. Standard series: eˣ = Σxᵏ/k!, sin x = x − x³/3! + x⁵/5! − …, cos x = 1 − x²/2! + x⁴/4! − …, ln(1 + x) = x − x²/2 + x³/3 − …, 1/(1 − x) = Σxᵏ. Lagrange error bound: |f(x) − Pₙ(x)| ≤ M·|x − a|ⁿ⁺¹/(n + 1)!, where M is the largest value of |f⁽ⁿ⁺¹⁾| between a and x.

Bound on the derivative

M = 1

Lagrange bound

|R₅| ≤ 1·0.3⁶/6! = 1.012 × 10⁻⁶

Answer

|R₅| = 1.012 × 10⁻⁶

The true error is smaller: |f(0.3) − P₅(0.3)| = 4.334 × 10⁻⁸.

5.Matrices & determinants

Answer: det A = −14

Matrices: the determinant of a 2×2 matrix is ad − bc. For 3×3, expand along a row: each entry times the determinant of the 2×2 matrix left after removing its row and column, with alternating signs + − +. Eigenvalues λ solve det(A − λI) = 0; for 2×2 that is λ² − (trace)·λ + det = 0.

2×2 minors of the first row

M₁₁ = −8, M₁₂ = −2, M₁₃ = 3

Cofactor expansion

det A = 2·(−8) − (−2)·(−2) + 2·3 = −14

Answer

det A = −14
6.Matrices & determinants

Answer: x = 5.429

Matrices: the determinant of a 2×2 matrix is ad − bc. For 3×3, expand along a row: each entry times the determinant of the 2×2 matrix left after removing its row and column, with alternating signs + − +. Eigenvalues λ solve det(A − λI) = 0; for 2×2 that is λ² − (trace)·λ + det = 0.

Determinant of the coefficient matrix

det A = (−2)·3 − 5·(−4) = 14

Replace the x column

det Aₓ = 7·3 − 5·(−11) = 76
x = 76/14 = 5.429

Answer

x = 5.429
y = 3.571
7.Differential equations

Answer: t = 2.235 min

First-order differential equations: dy/dt = k·y has the solution y = y₀·ekt (growth for k > 0, decay for k < 0); a half-life T gives k = ln 2/T. Newton's law of cooling, dT/dt = −k·(T − Tₐ), gives T(t) = Tₐ + (T₀ − Tₐ)·e−kt. A linear equation y′ + p(x)·y = q(x) is solved with the integrating factor μ = e∫p dx: (μy)′ = μq, so μy = ∫μq dx + C.

Cooling constant

k = ln(-24/-19)/6 = 0.03894 min⁻¹

Time to reach the target

t = ln(-24/(−22))/0.03894 = 2.235 min

Answer

t = 2.235 min
8.Differential equations

Answer: ymax = 2.19

Second-order linear equations: for y″ + b·y′ + c·y = 0 try y = ert: this gives the characteristic equation r² + b·r + c = 0. Two real roots r₁ ≠ r₂ give y = A·er₁t + B·er₂t (overdamped); a double root r gives y = (A + Bt)·ert (critically damped); complex roots −α ± jω give y = e−αt(A cos ωt + B sin ωt) (underdamped, oscillating). The initial values y(0) and y′(0) fix A and B. Written as y″ + 2ζωny′ + ωn²y = 0, ωn is the natural frequency and ζ the damping ratio: ζ < 1 oscillates. With a constant input, y″ + by′ + cy = c·K, the solution is the steady value K plus the free response.

Steady value and roots

yss = 2, r = −1.5 ± 2j

Constants from the initial values

y(0) = 2 + A = 0 → A = −2
y′(0) = −1.5A + 2B = 0 → B = −1.5

Peak

t = π/2 = 1.571
ymax = 2·(1 + e−1.5·π/2) = 2.19

Answer

ymax = 2.19

ExamProblems · examproblems.com/courses/numerical-methods