 Chapter 1: REVIEW OF WHOLE NUMBERS AND INTEGERS
 Chapter 11: PLACE VALUE AND OUR NUMBER SYSTEM
 Chapter 12: OPERATIONS WITH WHOLE NUMBERS AND INTEGERS
 Chapter 10: PAYROLL
 Chapter 101: GROSS PAY
 Chapter 102: PAYROLL DEDUCTIONS
 Chapter 103: THE EMPLOYERS PAYROLL TAXES
 Chapter 11: SIMPLE INTEREST AND SIMPLE DISCOUNT
 Chapter 111: THE SIMPLE INTEREST FORMULA
 Chapter 112: ORDINARY AND EXACT INTEREST
 Chapter 113: PROMISSORY NOTES
 Chapter 12: CONSUMER CREDIT
 Chapter 121: INSTALLMENT LOANS AND CLOSEDEND CREDIT
 Chapter 122: PAYING A LOAN BEFORE IT IS DUE: THE RULE OF 78
 Chapter 123: OPENEND CREDIT
 Chapter 13: COMPOUND INTEREST, FUTURE VALUE, AND PRESENT VALUE
 Chapter 131: COMPOUND INTEREST AND FUTURE VALUE
 Chapter 132: PRESENT VALUE
 Chapter 14: ANNUITIES AND SINKING FUNDS
 Chapter 141: FUTURE VALUE OF AN ANNUITY
 Chapter 142: SINKING FUNDS AND THE PRESENT VALUE OF AN ANNUITY
 Chapter 15: BUILDING WEALTH THROUGH INVESTMENTS
 Chapter 151: STOCKS
 Chapter 152: BONDS
 Chapter 153: MUTUAL FUNDS
 Chapter 16: MORTGAGES
 Chapter 161: MORTGAGE PAYMENTS
 Chapter 162: AMORTIZATION SCHEDULES AND QUALIFYING RATIOS
 Chapter 17: DEPRECIATION
 Chapter 171: DEPRECIATION METHODS FOR FINANCIAL STATEMENT REPORTING
 Chapter 172: DEPRECIATION METHODS FOR IRS REPORTING
 Chapter 18: INVENTORY
 Chapter 181: INVENTORY
 Chapter 182: TURNOVER AND OVERHEAD
 Chapter 19: INSURANCE
 Chapter 191: LIFE INSURANCE
 Chapter 192: PROPERTY INSURANCE
 Chapter 193: MOTOR VEHICLE INSURANCE
 Chapter 2: REVIEW OF FRACTIONS
 Chapter 21: FRACTIONS
 Chapter 22: ADDING AND SUBTRACTING FRACTIONS
 Chapter 23: MULTIPLYING AND DIVIDING FRACTIONS
 Chapter 20: TAXES
 Chapter 201: SALES TAX AND EXCISE TAX
 Chapter 202: PROPERTY TAX
 Chapter 203: INCOME TAXES
 Chapter 21: FINANCIAL STATEMENTS
 Chapter 211: THE BALANCE SHEET
 Chapter 212: INCOME STATEMENTS
 Chapter 213: FINANCIAL STATEMENT RATIOS
 Chapter 3: DECIMALS
 Chapter 31: DECIMALS AND THE PLACEVALUE SYSTEM
 Chapter 32: OPERATIONS WITH DECIMALS
 Chapter 33: DECIMAL AND FRACTION CONVERSIONS
 Chapter 4: BANKING
 Chapter 41: CHECKING ACCOUNT TRANSACTIONS
 Chapter 42: BANK STATEMENTS
 Chapter 5: EQUATIONS
 Chapter 51: EQUATIONS
 Chapter 52: USING EQUATIONS TO SOLVE PROBLEMS
 Chapter 53: FORMULAS
 Chapter 6: PERCENTS
 Chapter 61: PERCENT EQUIVALENTS
 Chapter 62: SOLVING PERCENTAGE PROBLEMS
 Chapter 63: INCREASES AND DECREASES
 Chapter 7: BUSINESS STATISTICS
 Chapter 71: GRAPHS AND CHARTS
 Chapter 72: MEASURES OF CENTRAL TENDENCY
 Chapter 73: MEASURES OF DISPERSION
 Chapter 8: TRADE AND CASH DISCOUNTS
 Chapter 81: SINGLE TRADE DISCOUNTS
 Chapter 82: TRADE DISCOUNT SERIES
 Chapter 83: CASH DISCOUNTS AND SALES TERMS
 Chapter 9: MARKUP AND MARKDOWN
 Chapter 91: MARKUP BASED ON COST
 Chapter 92: MARKUP BASED ON SELLING PRICE AND MARKUP COMPARISONS
 Chapter 93: MARKDOWN, SERIES OF MARKDOWNS, AND PERISHABLES
Business Math, 9th Edition  Solutions by Chapter
Full solutions for Business Math,  9th Edition
ISBN: 9780135108178
Business Math,  9th Edition  Solutions by Chapter
Get Full SolutionsThis textbook survival guide was created for the textbook: Business Math, , edition: 9. The full stepbystep solution to problem in Business Math, were answered by , our top Math solution expert on 03/08/18, 08:36PM. Business Math, was written by and is associated to the ISBN: 9780135108178. Since problems from 77 chapters in Business Math, have been answered, more than 31613 students have viewed full stepbystep answer. This expansive textbook survival guide covers the following chapters: 77.

Adjacency matrix of a graph.
Square matrix with aij = 1 when there is an edge from node i to node j; otherwise aij = O. A = AT when edges go both ways (undirected). Adjacency matrix of a graph. Square matrix with aij = 1 when there is an edge from node i to node j; otherwise aij = O. A = AT when edges go both ways (undirected).

Big formula for n by n determinants.
Det(A) is a sum of n! terms. For each term: Multiply one entry from each row and column of A: rows in order 1, ... , nand column order given by a permutation P. Each of the n! P 's has a + or  sign.

Column picture of Ax = b.
The vector b becomes a combination of the columns of A. The system is solvable only when b is in the column space C (A).

Companion matrix.
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 nl  An).

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

Dot product = Inner product x T y = XI Y 1 + ... + Xn Yn.
Complex dot product is x T Y . Perpendicular vectors have x T y = O. (AB)ij = (row i of A)T(column j of B).

Factorization
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.

Full column rank r = n.
Independent columns, N(A) = {O}, no free variables.

Incidence matrix of a directed graph.
The m by n edgenode incidence matrix has a row for each edge (node i to node j), with entries 1 and 1 in columns i and j .

Kirchhoff's Laws.
Current Law: net current (in minus out) is zero at each node. Voltage Law: Potential differences (voltage drops) add to zero around any closed loop.

Length II x II.
Square root of x T x (Pythagoras in n dimensions).

Linear combination cv + d w or L C jV j.
Vector addition and scalar multiplication.

Minimal polynomial of A.
The lowest degree polynomial with meA) = zero matrix. This is peA) = det(A  AI) if no eigenvalues are repeated; always meA) divides peA).

Multiplier eij.
The pivot row j is multiplied by eij and subtracted from row i to eliminate the i, j entry: eij = (entry to eliminate) / (jth pivot).

Network.
A directed graph that has constants Cl, ... , Cm associated with the edges.

Projection matrix P onto subspace S.
Projection p = P b is the closest point to b in S, error e = b  Pb is perpendicularto S. p 2 = P = pT, eigenvalues are 1 or 0, eigenvectors are in S or S...L. If columns of A = basis for S then P = A (AT A) 1 AT.

Random matrix rand(n) or randn(n).
MATLAB creates a matrix with random entries, uniformly distributed on [0 1] for rand and standard normal distribution for randn.

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

Stiffness matrix
If x gives the movements of the nodes, K x gives the internal forces. K = ATe A where C has spring constants from Hooke's Law and Ax = stretching.

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