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 monthlong 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
This course is intended to provide students with the skills necessary to digest, critique, and express every-day statistics and to use statistical thinking to answer questions in their own lives. Students will be exposed to and produce descriptive statistics, including measures of central tendency & spread, as well as common visual representations of data. The bulk of the class will be devoted to giving students the tools needed to analyze and critique statistical claims, including an understanding of the dangers of confounding variables and bias, the advantages and limitations of various study designs and statistical inference, and how to carefully read and parse claims which attempt to use numbers to sway their audience. The class will examine this material in authentic contexts such as political polling, medical decision making, online dating, and personal finance. This course is primarily aimed at students whose majors do not require mathematics or statistics.
(QR 150 and STAT 150 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 but should expect to put in additional effort to learn this skill. (QR 309 and STAT 309 are cross-listed courses.) -
This course is intended to provide students with the skills necessary to digest, critique, and express every-day statistics and to use statistical thinking to answer questions in their own lives. Students will be exposed to and produce descriptive statistics, including measures of central tendency & spread, as well as common visual representations of data. The bulk of the class will be devoted to giving students the tools needed to analyze and critique statistical claims, including an understanding of the dangers of confounding variables and bias, the advantages and limitations of various study designs and statistical inference, and how to carefully read and parse claims which attempt to use numbers to sway their audience. The class will examine this material in authentic contexts such as political polling, medical decision making, online dating, and personal finance. This course is primarily aimed at students whose majors do not require mathematics or statistics. (QR 150 and STAT 150 are cross-listed courses.)
Quantitative Reasoning Program
106 Central Street
Wellesley, MA 02481