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1 Instructor: Bon Crowder Mathematics Spring Branch Math 1324: Finite Mathematics with Applications CRN Spring 2014 Room am - 12:30 TTh 3 hour lecture course / 48 hours per semester/ 15 weeks Textbook: Mathematics with Applications; 10th ed.; Lial, Margaret L ISBN-13: Instructor Contact Information: Office location and hours: by appointment and during lab hours: Th 9:30-10:30 and MW 3pm - 3:30 (starting Feb 10) Course Description MATH 1324: Finite Mathematics with Applications. A survey of finite mathematics and its application to problems of business and the natural and social sciences. Topics include set theory, probability, an introduction to matrices, linear programming, and an introduction to statistics. Prerequisites A grade of C or better in Math 1314 or the equivalent. Course Goal This course is intended for students majoring in liberal arts and secondary education. Course Student Learning Outcomes (SLO): 1. Solve business / financial problems by the use of systems of equations, systems of inequalities, and matrices. 2. Formulate and solve linear programming problems by graphing and the Simplex Method. 3. Analyze information and make conclusions based on set data. 4. Comprehend, analyze, and synthesize statistical data in order to make predictions. Learning outcomes Students will: 1.1 Be able to graph systems of linear equations in two variables. 1.2 Be able to solve systems of linear equations using Gauss-Jordan elimination. 1.3 Know how to add, subtract, and multiply matrices. 1.4 Be able to find the inverse of a square matrix. 1.5 Be able to graph systems of linear inequalities in two variables. 2.1 Know the graphical method for solving a linear programming problem. 2.2 Know the simplex method for solving standard maximization and standard minimization problems. 3.1 Be able to perform the basic set operations. 3.2 Be able to use the multiplication principle of counting. 3.3 Understand permutations and combinations. 3.4 Be able to use the basic counting techniques. 4.1 Understand conditional probability. 4.2 Be able to use Bayes Formula. 4.3 Be able to find expected values. 4.4 Be able to find the standard deviation of a set of values. 4.5 Be able to find the binomial distribution and the normal distribution of a set of data. Instructional Methods This class is taught in the format of interactive lecture. Your attendance is required, your participation is encouraged. If you d like a copy of my teaching philosophy, please me and I ll forward one to you.

2 CALENDAR Below is the course flow. Attend class regularly to make sure you have the latest information on exam dates and scheduling. UNIT I Review (3 hours) 1/2 hour Introduction to the course 1/2 hour 2.1 Graphs 1 hour 2.2 Equations of Lines 1 hour 2.4 Linear Inequalities UNIT II Systems of Linear Equations (8 hours) 1 1/2 hours 6.1 Systems of Linear Equations 2 hours 6.2 The Gauss-Jordan Method 1 1/2 hours 6.3 Basic Matrix Operations 2 hours 6.4 Matrix Products and Inverses 1 hour 6.5 Applications of Matrices (Omit Code Theory and Routing) UNIT III Linear Programming (9 hours) 1/2 hour 7.1 Graphing Linear Inequalities in Two Variables 1 1/2 hours 7.2 Linear Programming: The Graphical Method 1 1/2 hours 7.3 Applications of Linear Programming 1 1/2 hours 7.4 The Simplex Method: Maximization 1 1/2 hours 7.5 Maximization Applications 1 1/2 hours 7.6 The Simplex Method: Duality and Minimization 1 hour 7.7 The Simplex Method: Nonstandard Problems UNIT IV Sets and Probability (8.5 hours) 1 hour 8.1 Sets 1 1/2 hours 8.2 Applications of Venn Diagrams 1 1/2 hours 8.3 Introduction to Probability 1 1/2 hours 8.4 Basic Concepts of Probability 2 hours 8.5 Conditional Probability and Independent Events 1 hour 8.6 Bayes Formula UNIT V Counting, Probability Distributions, and Further Topics in Probability (7.5 hours) 1 1/2 hours 9.1 Probability Distributions and Expected Value 1 1/2 hours 9.2 The Multiplication Principle, Permutations, and Combinations 1 1/2 hours 9.3 Applications of Counting 1 1/2 hours 9.4 Binomial Probability 1 1/2 hours 9.5 Markov Chains (Optional) UNIT VI Introduction to Statistics (6 hours) 1 1/2 hour 10.1 Frequency Distributions and Measures of Central Tendency 1 1/2 hour 10.2 Measures of Variance 1 1/2 hours 10.3 Normal Distributions 1 1/2 hours 10.4 Normal Approximation to the Binomial Distribution Student Assignments & Assessments Grade Calculation Final Grade Scale Final Exam - 30% Exam 1-25% Exam 2-25% Exam 3-20% = A = B = C = D Below 60 = F Page 2 of 5

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