- Chapter 1: Identify Points, Lines, and Planes
- Chapter 10: Use Properties of Tangents
- Chapter 11: Areas of Triangles and Parallelograms
- Chapter 12: Explore Solids
- Chapter 2: Use Inductive Reasoning
- Chapter 3: Identify Pairs of Lines and Angles
- Chapter 4: Apply Triangle Sum Properties
- Chapter 5: Midsegment Theorem and Coordinate Proof
- Chapter 6: Ratios, Proportions, and the Geometric Mean
- Chapter 7: Apply the Pythagorean Theorem
- Chapter 8: Find Angle Measures in Polygons
- Chapter 9: Translate Figures and Use Vectors
Geometry (Holt McDougal Larson Geometry) 1st Edition - Solutions by Chapter
Full solutions for Geometry (Holt McDougal Larson Geometry) | 1st Edition
Put CI, ... ,Cn in row n and put n - 1 ones just above the main diagonal. Then det(A - AI) = ±(CI + c2A + C3A 2 + .•. + cnA n-l - An).
Cross product u xv in R3:
Vector perpendicular to u and v, length Ilullllvlll sin el = area of parallelogram, u x v = "determinant" of [i j k; UI U2 U3; VI V2 V3].
S. Permutation with S21 = 1, S32 = 1, ... , finally SIn = 1. Its eigenvalues are the nth roots e2lrik/n of 1; eigenvectors are columns of the Fourier matrix F.
Determinant IAI = det(A).
Defined by det I = 1, sign reversal for row exchange, and linearity in each row. Then IAI = 0 when A is singular. Also IABI = IAIIBI and
Dimension of vector space
dim(V) = number of vectors in any basis for V.
A(B + C) = AB + AC. Add then multiply, or mUltiply then add.
A = L U. If elimination takes A to U without row exchanges, then the lower triangular L with multipliers eij (and eii = 1) brings U back to A.
A symmetric matrix with eigenvalues of both signs (+ and - ).
Linearly dependent VI, ... , Vn.
A combination other than all Ci = 0 gives L Ci Vi = O.
Markov matrix M.
All mij > 0 and each column sum is 1. Largest eigenvalue A = 1. If mij > 0, the columns of Mk approach the steady state eigenvector M s = s > O.
Pseudoinverse A+ (Moore-Penrose inverse).
The n by m matrix that "inverts" A from column space back to row space, with N(A+) = N(AT). A+ A and AA+ are the projection matrices onto the row space and column space. Rank(A +) = rank(A).
Row picture of Ax = b.
Each equation gives a plane in Rn; the planes intersect at x.
Similar matrices A and B.
Every B = M-I AM has the same eigenvalues as A.
Special solutions to As = O.
One free variable is Si = 1, other free variables = o.
Spectral Theorem A = QAQT.
Real symmetric A has real A'S and orthonormal q's.
Standard basis for Rn.
Columns of n by n identity matrix (written i ,j ,k in R3).
Constant down each diagonal = time-invariant (shift-invariant) filter.
Unitary matrix UH = U T = U-I.
Orthonormal columns (complex analog of Q).
Vector v in Rn.
Sequence of n real numbers v = (VI, ... , Vn) = point in Rn.
Stretch and shift the time axis to create Wjk(t) = woo(2j t - k).