Quantitative reasoning refers to the ability to understand, evaluate and use quantitative information. Quantitative information takes many forms, and quantitative reasoning skills span a vast spectrum from basic numerical manipulations to advanced statistics and mathematics. One three-credit course is required to ensure that students possess these necessary skills. Students scoring a 4 or 5 on the Calculus AB, Calculus BC or Statistics Advanced Placement tests will place out of this requirement. Math placement testing is also available through SMU’s mathematics departmental examinations.
MATH 1307. Introduction to Mathematical Sciences.
Permutations and combinations, probability, Markov chains, linear programming,
elementary statistics, and mathematics of finance.
Prerequisite: High School Algebra.
MATH 1309. Introduction to Calculus for Business and Social Science. Derivatives and integrals of algebraic, logarithmic, and exponential functions with applications to the time value of money, curve sketching, maximum-minimum problems, and computation of areas. Applications to business and economics. (Natural science and engineering students must take MATH 1337. Credit not allowed for both MATH 1309 and MATH 1337.) Prerequisite: Placement out of MATH 1303 or a grade of C- or higher in MATH 1303.
MATH 1337. Calculus with Analytic Geometry I. Differential and integral calculus for algebraic, trigonometric functions, and transcendental functions, with applications to curve sketching, velocity, maximum-minimum problems, areas, and volumes. (Credit not allowed for both MATH 1309 and MATH 1337.) Prerequisite: Placement out of MATH 1304 or a grade of C- or higher in Math 1304.
STAT 1301. Introduction to Statistics. Introduction to collecting observations and measurements, organizing data, variability, and fundamental concepts and principles of decision-making. Emphasis is placed on statistical reasoning and the uses and misuses of statistics. No prerequisite.
STAT 2301. Statistics for Modern Business Decisions. A foundation in data analysis and probability models is followed by elementary applications of condence intervals, hypothesis testing, correlation, and regression.
STAT 2331. Introduction to Statistical Methods. An introduction to statistics for behavioral, biological, and social scientists. Topics include descriptive statistics, probability and inferential statistics including hypothesis testing, and contingency tables.
Quantitative Foundation: Student Learning Outcomes
1. Students will be able to interpret mathematical models such as formulas, graphs, tables, and schematics.
2. Students will be able to solve problems using algebraic, geometric, calculus, statistical and/or computational methods.
3. Students will be able to determine correctness, reasonableness, identify alternatives, and select optimal results in mathematical problems.
4. Students will be able to draw inferences from mathematical models in the various forms listed above.
5. Students will be able to present calculations and results in a clear and concise manner.