Liberal Arts Math Continuum

The following is a list of courses suggested for most liberal arts majors. These courses may be used satisfy a general education requirement. All courses have a recommended Math Placement Test score of 420.

New SAT scores apply to scores dated beginning in 2019.

MATH1006 Introduction to Mathematical Reasoning

  • 3 Undergraduate Credits
  • Prerequisite: 420 Math Placement Test recommended
  • The course begins with a study of Polya's four-step problem solving method. We explore sets and use Venn's diagrams to discover properties of set operations. Students use this knowledge to model operations with numbers and analyze properties of different number systems. Students will use mathematical reasoning and the Polya problem solving process to solve various real world problems and interpret their solutions.

MATH1008 Foundations of Quantitative Reasoning

  • 3 Undergraduate Credits
  • Prerequisite: 420 Math Placement Test recommended
  • Project-based course, emphasizing problem-solving, model-building, and basic data manipulation in real world contexts. Topics include: problem-solving, statistical reasoning, linear and exponential modeling, and modeling with geometry.

MATH1012 Mathematics in Management Science

  • 3 Undergraduate Credits
  • Prerequisite: 420 Math Placement Test recommended
  • A quantitative reasoning course designed for the students in the liberal arts and the fine arts. This course uses graphs, networks, and diagrams to model and solve real life problems such as designing routes, planning itineraries, scheduling complex tasks, and optimizing the use of resources to meet business, government, and individual goals. These methods provide good solutions to problems that are intractably hard to solve perfectly, like how UPS drivers should efficiently schedule the deliveries of packages in their trucks. UPS used the techniques studied in this course to redesign their routes and save 3 million gallons of gas in 2006. Some of these techniques have also been used by artists to create works of art.

MATH1014 Mathematics of Social Choice

  • 3 Undergraduate Credits
  • Prerequisite: 420 Math Placement Test recommended
  • A quantitative reasoning course for students in the liberal arts. Contains the study of voting systems and fair division, apportionment using divisor methods, and game theory.

STAT1031 Introduction to Statistics

  • 3 Undergraduate Credits
  • Prerequisite: 420 Math Placement Test recommended
  • A one-semester comprehensive introduction to statistics suitable for students in biology, nursing, allied health, and applied science. Discussion of data, frequency distributions, graphical and numerical summaries, design of statistical studies, and probability as a basis for statistical inference and prediction. The concepts and practice of statistical inference including confidence intervals, one and two sample t-tests, chi-square tests, regression and analysis of variance, with attention to selecting the procedure(s) appropriate for the question and data structure, and interpreting and using the result.

STAT1034 Elementary Statistics I

  • 3 Undergraduate Credits
  • Prerequisite: 420 Math Placement Test recommended
  • An introduction to statistics for students without a calculus background. The course covers data analysis (numerical summaries and graphics for describing and displaying the distributions of numerical and categorical data), the basic principles of data collection from samples and experiments, elementary probability, the application of the normal distribution to the study of random samples, statistical estimation (construction and interpretation of one sample confidence intervals), and an introduction to hypothesis testing (the structure of one sample hypothesis tests and the logic of using them to make decisions).
  • Following this course, students may take STAT1035 ELEMENTARY STATISTICS II 

STAT1035 Elementary Statistics II

  • 3 Undergraduate Credits
  • Prerequisite: STAT 1034 Elementary Statistics I
  • An introduction to inferential statistics for students without a calculus background. The coursecovers one and two-sample hypothesis tests for means and proportions, chi-squared tests, linear regression, analysis of variance, and non-parametric tests based on ranks, with attention to selecting the procedure(s) appropriate for the question and data structure, and interpreting the results.