Includes index

Part 1 Sets and lines: sets; linear equations. Part 2 Matrices: matrix operations; applications. Part 3 Systems of linear equations: Gauss elimination; Gauss-Jordan elimination; echelon and reduced echelon forms; systems with non-unique solutions. Part 4 Matrix inverses and LU factors: matrix inverses; LU factors. Part 5 Introductory linear programming: systems of linear inequalities; linear programming problems with two variables; geometric solutions to two variable LP problems; the simplex method. Part 6 Intermediate linear programming: non-standard form LP problems; the big-M method; infeasible, unbounded and non-unique solutions; solving applied problems. Part 7 Advanced linear programming: dual simplex method; duality; sensitivity analysis; interpreting LP reports. Part 8 Counting: the exclusion-exclusion principle and venn diagrams; the fundamental counting principle; permutations; combinations; additional counting techniques. Part 9 Probability: basic concepts of probability; conditional probability - independent events; Bayes' formula; Bernoulli trials; Markov processes; regular Markov chains; absorbing Markov chains. Part 10 Statistics: frequency distributions, probability distributions and histograms; finding the centre - medians, means and expected values; measuring the spread - variance and standard deviation; normal distributions; approximating binomial random variables with normal random variables; linear regression. Part 11 Mathematics of finance: simple and compound interest; annuities; amortization; modelling financial problems with LP. Part 12 Logic: statements and truth tables; implications and logical equivalence; conditional statements and valid arguments