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.
For a table value: interpolate linearly between the two neighbouring points.
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.
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
Identify the type: arithmetic (constant difference), geometric (constant ratio), a standard series, a power series or a Taylor polynomial.
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.
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.
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
Approximate ∫02 sin x dx with Simpson's rule, n = 2, and compare it with the exact value. Find the absolute error |E| = |S − I|.
f(x) = sin x[a, b] = [0, 2]n = 2
|E| =
2.Numerical methodsHard
Solve y′ = y(2 − y), y(0) = 1 with Euler's method and step h = 0.1 up to t = 0.4. The exact solution is y = 2y₀/(y₀ + (2 − y₀)e−2t). Find the global error |E| = |y(0.4) − y4|.
y′ = y(2 − y)y(0) = 1h = 0.1
|E| =
3.Sequences & seriesMedium
Find the radius of convergence R of the power series Σk=1∞ k²·3ᵏ·(x − 2)ᵏ.
Σ k²·3ᵏ·(x − 2)ᵏx₀ = 2
R =
4.Sequences & seriesHard
f(x) = sin x is approximated at x = 2 by its Maclaurin polynomial of degree n. With the Lagrange bound M·|x|ⁿ⁺¹/(n + 1)! and M = 1, find the smallest degree n that guarantees an error below 1 × 10⁻⁶.
f(x) = sin xx = 2M = 1ε = 1 × 10⁻⁶
n =
5.Matrices & determinantsMedium
Find the determinant det A of the 3×3 matrix A shown.
A = [−1 −1 −1; −5 −4 −5; −4 −5 0]
det A =
6.Matrices & determinantsHard
Solve the system −6x − 2y = −10 and −x + 6y = 5. Find x.
−6x − 2y = −10−x + 6y = 5
x =
7.Differential equationsMedium
Solve y″ + 8y′ + 15y = 0 with y(0) = 2 and y′(0) = -2. Find y(1).
y″ + 8y′ + 15y = 0y(0) = 2y′(0) = -2
y(1) =
8.Differential equationsHard
Solve y″ + y′ + 25.25y = 0 with y(0) = 5 and y′(0) = 0 (released from rest). Find y(0.5); angles in radians.
y″ + y′ + 25.25y = 0y(0) = 5y′(0) = 0
y(0.5) =
3Solutions
1.Numerical methods
Answer: |E| = 0.008914
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.
Exact value
I = 1.416147
Simpson's rule
S = (1/3)·(0 + 4·0.841471 + 0.909297) = 1.42506
Error
|E| = |1.42506 − 1.416147| = 0.008914
Answer
|E| = 0.008914
Relative error: 0.6294%.
2.Numerical methods
Answer: |E| = 0.006386
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.
Euler steps
y4 = 1.386335
Exact value
y(0.4) = 1.379949
Global error
|E| = |1.379949 − 1.386335| = 0.006386
Graph
Answer
|E| = 0.006386
Halving h roughly halves the error of Euler's method.
3.Sequences & series
Answer: R = 0.3333
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 = (1/3)·(k/(k + 1))² → 1/3
Radius
R = 0.3333
Answer
R = 0.3333
The ratio test says nothing at the two end points; they have to be checked separately.
4.Sequences & series
Answer: n = 13
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.
Bounds for increasing n
n = 12: 1.316 × 10⁻⁶ ≥ 1 × 10⁻⁶
n = 13: 1.879 × 10⁻⁷ < 1 × 10⁻⁶
Smallest degree
n = 13
Answer
n = 13
5.Matrices & determinants
Answer: det A = −4
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 = −25, M₁₂ = −20, M₁₃ = 9
Cofactor expansion
det A = (−1)·(−25) − (−1)·(−20) + (−1)·9 = −4
Answer
det A = −4
6.Matrices & determinants
Answer: x = 1.316
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 = (−6)·6 − (−2)·(−1) = −38
Replace the x column
det Aₓ = (−10)·6 − (−2)·5 = −50
x = −50/(−38) = 1.316
Answer
x = 1.316
y = 1.053
7.Differential equations
Answer: y(1) = 0.1857
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.
Characteristic roots
(r + 3)(r + 5) = 0 → r = −3, −5
Constants from the initial values
A + B = 2, −3A − 5B = -2
A = 4, B = −2
Evaluate
y(1) = 4·e−3 + (−2)·e−5 = 0.1857
Answer
y(1) = 0.1857
8.Differential equations
Answer: y(0.5) = −2.887
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.