Mission Statement & Department Learning Goals

Instruction in this department is intended to aid in the development of exact, concise and independent reasoning, to cultivate the imagination and to inspire habits of original and independent thought.

Mission & Value Statement

The department of Mathematics, Computer Science, and Statistics helps St. Lawrence students develop their quantitative, logical, computational, and analytical abilities. We believe that these skills are meaningfully interrelated, deeply rewarding to pursue, and widely needed in the modern world.

Every student is welcome here! If you are contemplating a major or minor in our department, we want to help you build a strong foundation for the many potential careers and graduate programs that await you. If you are taking a course to satisfy a requirement, or just for fun, we want to help you acquire intellectual tools that will aid you along your chosen path.

No matter what your reason for being here, we want to make sure you have the support to succeed, and we want you to feel at home in our classrooms. We accommodate a wide variety of student backgrounds and work to find the right courses for every student. Recognizing that past and current injustice has turned far too many people away from our disciplines, we are committed to fostering a diverse and inclusive community.

Mathematics Major Learning Goals

Majors in mathematics should be able to:

  1. Apply mathematical techniques to articulate and prove statements related to sets, spaces, functions, and operations.
  2. Articulate ideas using the symbolic language of mathematics.
  3. Use and design mathematical models to solve problems and interpret results appropriately.
  4. Effectively communicate—both in writing and orally—mathematical concepts to technical and non-technical audiences.
  5. Demonstrate an awareness of the impact of quantitative literacy and mathematical thinking on society and global issues.

Computer Science Major Learning Goals

Majors in Computer Science should be able to:

  1. Design and construct non-trivial software systems in multiple programming languages through the use of modern tools, specifications, and testing.
  2. Apply a broad range of problem-solving techniques to develop algorithmic solutions to computational problems.
  3. Propose multiple implementations for a given task and evaluate—especially with respect to performance and hardware constraints—their relative advantages and disadvantages.
  4. Investigate the cause and location of defects in software and implement robust fixes without introducing new faults.
  5. Effectively communicate—both in writing and orally—computational processes and software design choices to other practitioners and the general public.
  6. Discuss the impact of computers and computation on society in the past, present, and future.

Statistics Major Learning Goals

Majors in Statistics should be able to:

  1. Use appropriate statistical techniques to address real questions with data, with emphasis on articulating appropriate practical results.
  2. Build, assess, and interpret appropriate statistical models using statistical software.
  3. Recognize the importance of proper data collection, the need for ethical treatment of subjects, and the possibility of biases in any statistical analyses.
  4. Describe the theoretical underpinnings of statistical estimation and inference.
  5. Effectively communicate—both in writing and orally— the methods and results of statistical analyses and applications to other practitioners as well as to the general public. 

Data Science Major Learning Goals

Majors in Data Science should be able to:

  1. Apply appropriate computational techniques to organize and process data.
  2. Apply appropriate statistical methodologies to collect, analyze, and interpret data.
  3. Use modern computational and analytical tools to build data-driven applications.
  4. Effectively communicate—visually, in writing, and orally —the methods and results of data science projects to other practitioners as well as the general public.
  5. Assess the human impacts of data science and evaluate them in terms of bias, fairness, and justice.

Learning Goals for Non-Majors in Departmental Courses

All students who take a course in our department should be able to:

  1. Investigate and answer questions using the methods taught in the course and be able to clearly interpret the results.
  2. Develop an understanding of the ideas taught in the course sufficiently to apply them effectively in other situations.
  3. Appreciate both the beauty and the importance of the discipline.