Quantitative Reasoning
Academic Program Introduction
The Quantitative Reasoning Program oversees the quantitative reasoning and data literacy requirement. We do not offer a major or minor.
Through the program, students develop mathematical, logical, and statistical problem-solving tools. Most academic fields, many professions, and a lot of ordinary, everyday tasks draw upon quantitative reasoning. In data literacy classes, students practice statistical analysis and data interpretation within a specific discipline.
Learning goals
Use logic, mathematics, and statistics to make decisions as students, consumers, and citizens.
Construct questions that can be answered with data, and choose appropriate methods for collecting and analyzing relevant data to address these questions.
Opportunities
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Celebrating QR Connections series
Sponsored by Ellen Genat Hoffman ’68 and Stephen G. Hoffman, the series recognizes the connection between quantitative reasoning and various disciplines with three to five events, such as lectures, panels, debates, and hands-on workshops.
Course highlights
Introduction to Quantitative Reasoning
QR140
In this course, students develop and apply mathematical, logical, and statistical skills to solve problems in authentic contexts. The quantitative skills emphasized include algebra, geometry, probability, statistics, estimation, and mathematical modeling. Throughout the course, these skills are used to solve real world problems, from personal finance to medical decision-making. A student passing this course satisfies the Quantitative Reasoning (QR) component of the Quantitative Reasoning & Data Literacy requirement. This course is required for students who do not satisfy the QR component of the QR & DL requirement via the Quantitative Reasoning Assessment. Those who satisfy the QR Assessment, but still want to enroll in this course must receive permission of instructor.
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Applied Data Analysis and Statistical Inference
QR260
This is an intermediate statistics course focused on fundamentals of statistical inference and applied data analysis tools. Emphasis on thinking statistically, evaluating assumptions, and developing practical skills for real-life applications to fields such as medicine, politics, education, and beyond. Topics include t-tests and non-parametric alternatives, analysis of variance, linear regression, model refinement and missing data. Students can expect to gain a working knowledge of the statistical software R, which will be used for data analysis and for simulations designed to strengthen conceptual understanding. This course can be counted toward the major or minor in Mathematics, Statistics, Data Science, Economics, Environmental Studies, Psychology or Neuroscience. Students who earned a Quantitative Analysis Institute Certificate are not eligible for this course.. Enrollment in this course is by permission of the instructor only. Students who are interested in taking this course should fill out this Google Form. (QR 260 and STAT 260 are cross-listed courses.) -
Causal Inference
QR309
This course focuses on statistical methods for causal inference, with an emphasis on how to frame a causal (rather than associative) research question and design a study to address that question. What implicit assumptions underlie claims of discrimination? Why do we believe that smoking causes lung cancer? We will cover both randomized experiments – the history of randomization, principles for experimental design, and the non-parametric foundations of randomization-based inference – and methods for drawing causal conclusions from non-randomized studies, such as propensity score matching. Students will develop the expertise necessary to assess the credibility of causal claims and master the conceptual and computational tools needed to design and analyze studies that lead to causal inferences. Examples will come from economics, psychology, sociology, political science, medicine, and beyond. Previous exposure to the statistical software R is expected; students who have not previously coded in R may enroll with permission of the instructor but should expect to put in additional effort to learn this skill. (QR 309 and STAT 309 are cross-listed courses.)
106 Central Street
Wellesley, MA 02481