 Chapter 1: QUADRATIC EQUATIONS
 Chapter 10: PERIODIC BEHAVIOUR
 Chapter 11: TRIGONOMETRIC EQUATIONS
 Chapter 12: VECTORS AND SCALARS
 Chapter 13: PROBLEMS INVOLVING VECTOR OPERATIONS
 Chapter 14: LIMITS
 Chapter 15: Rules of differentiation
 Chapter 16: Properties of curves
 Chapter 17: Applications of differential calculus
 Chapter 18: Integration
 Chapter 19: Applications of integration
 Chapter 2: RELATIONS AND FUNCTIONS
 Chapter 20: Descriptive statistics
 Chapter 21: Linear modelling
 Chapter 22: Probability
 Chapter 23: Discrete random variables
 Chapter 24: The normal distribution
 Chapter 25: Miscellaneous questions
 Chapter 3: EXPONENTS
 Chapter 4: LOGARITHMS IN BASE 10
 Chapter 5: GRAPHING FUNCTIONS
 Chapter 6: NUMBER SEQUENCES
 Chapter 7: BINOMIAL EXPANSIONS
 Chapter 8: RADIAN MEASURE
 Chapter 9: AREAS OF TRIANGLES
Mathematics for the International Student: Mathematics SL 3rd Edition  Solutions by Chapter
Full solutions for Mathematics for the International Student: Mathematics SL  3rd Edition
ISBN: 9781921972089
Mathematics for the International Student: Mathematics SL  3rd Edition  Solutions by Chapter
Get Full SolutionsSince problems from 25 chapters in Mathematics for the International Student: Mathematics SL have been answered, more than 21769 students have viewed full stepbystep answer. This textbook survival guide was created for the textbook: Mathematics for the International Student: Mathematics SL, edition: 3. Mathematics for the International Student: Mathematics SL was written by and is associated to the ISBN: 9781921972089. The full stepbystep solution to problem in Mathematics for the International Student: Mathematics SL were answered by , our top Math solution expert on 03/15/18, 06:04PM. This expansive textbook survival guide covers the following chapters: 25.

Affine transformation
Tv = Av + Vo = linear transformation plus shift.

Basis for V.
Independent vectors VI, ... , v d whose linear combinations give each vector in V as v = CIVI + ... + CdVd. V has many bases, each basis gives unique c's. A vector space has many bases!

Cofactor Cij.
Remove row i and column j; multiply the determinant by (I)i + j •

Column space C (A) =
space of all combinations of the columns of A.

Complete solution x = x p + Xn to Ax = b.
(Particular x p) + (x n in nullspace).

Cramer's Rule for Ax = b.
B j has b replacing column j of A; x j = det B j I det A

Fast Fourier Transform (FFT).
A factorization of the Fourier matrix Fn into e = log2 n matrices Si times a permutation. Each Si needs only nl2 multiplications, so Fnx and Fn1c can be computed with ne/2 multiplications. Revolutionary.

Free variable Xi.
Column i has no pivot in elimination. We can give the n  r free variables any values, then Ax = b determines the r pivot variables (if solvable!).

Inverse matrix AI.
Square matrix with AI A = I and AAl = I. No inverse if det A = 0 and rank(A) < n and Ax = 0 for a nonzero vector x. The inverses of AB and AT are B1 AI and (AI)T. Cofactor formula (Al)ij = Cji! detA.

Jordan form 1 = M 1 AM.
If A has s independent eigenvectors, its "generalized" eigenvector matrix M gives 1 = diag(lt, ... , 1s). The block his Akh +Nk where Nk has 1 's on diagonall. Each block has one eigenvalue Ak and one eigenvector.

Lucas numbers
Ln = 2,J, 3, 4, ... satisfy Ln = L n l +Ln 2 = A1 +A~, with AI, A2 = (1 ± /5)/2 from the Fibonacci matrix U~]' Compare Lo = 2 with Fo = O.

Normal matrix.
If N NT = NT N, then N has orthonormal (complex) eigenvectors.

Pascal matrix
Ps = pascal(n) = the symmetric matrix with binomial entries (i1~;2). Ps = PL Pu all contain Pascal's triangle with det = 1 (see Pascal in the index).

Permutation matrix P.
There are n! orders of 1, ... , n. The n! P 's have the rows of I in those orders. P A puts the rows of A in the same order. P is even or odd (det P = 1 or 1) based on the number of row exchanges to reach I.

Row picture of Ax = b.
Each equation gives a plane in Rn; the planes intersect at x.

Saddle point of I(x}, ... ,xn ).
A point where the first derivatives of I are zero and the second derivative matrix (a2 II aXi ax j = Hessian matrix) is indefinite.

Skewsymmetric matrix K.
The transpose is K, since Kij = Kji. Eigenvalues are pure imaginary, eigenvectors are orthogonal, eKt is an orthogonal matrix.

Standard basis for Rn.
Columns of n by n identity matrix (written i ,j ,k in R3).

Subspace S of V.
Any vector space inside V, including V and Z = {zero vector only}.

Toeplitz matrix.
Constant down each diagonal = timeinvariant (shiftinvariant) filter.