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Mathematics and Social Sciences


7. First-Year Seminar in Mathematics and Social Sciences

Consult special listings

15. Introduction to Data Analysis

10F, 11S, 11F, 12S: 9L

Methods for transforming raw facts into useful information. Directed toward students with an aptitude for mathematics. Emphasis is placed on the understanding, use, and both oral and written interpretation of exploratory data analysis within the rules of scientific method. With permission from the responsible department, MSS 15 may be used to satisfy some pre-medical, natural science, and social science departmental requirements in mathematics, statistics, and methodology. Limited enrollment.

Prerequisite: Mathematics 3 or higher, or permission. Dist: QDS. Levine.

36. Mathematical Models in the Social Sciences (Identical to Mathematics 36)

10F, 11F: 2A

Disciplines such as anthropology, economics, sociology, psychology, and linguistics all now make extensive use of mathematical models, using the tools of calculus, probability, game theory, network theory, often mixed with a healthy dose of computing. This course introduces students to a range of techniques using current and relevant examples. Students interested in further study of these and related topics are referred to the courses listed in the Mathematics and Social Sciences program.

Prerequisite: Mathematics 13, 20. Dist: TAS. Pauls.

41. Analysis of Social Networks

10F, 11F: Arrange

Students will gather and analyze data on a variety of networks (institutions, communities, elites, friendship systems, kinship systems, trade networks, and the like). Techniques of analysis may include graph theory, text analysis, multidimensional scaling and cluster analysis, and a variety of special models. Not limited to students in the major.

Prerequisite: Mathematics 3 or 6 and some knowledge of statistics, or permission of the instructor. Dist: QDS.

43. Mathematical Psychology

Not offered in the period from 10F through 12S

A course in mathematical models in psychology with emphasis on psychological foundations, applications, and testing. Topics will be chosen from information theory and its applications in memory, learning, language, and identification under uncertainty; probabilistic learning models; bargaining and its relation to n-person game theory; decision making under uncertainty; and thresholds and signal detectability.

Prerequisite: Psychology 1, and Mathematics 3 or 6. Permission required.

45. Data Analysis

11S, 12S: Arrange

Examination of the assumptions and interpretation of basic quantitative methods in the social sciences. Methods examined may include linear models, tabular analysis, and Tukey-Mosteller exploratory data analysis. Applications will be wide-ranging and customized to student research. Prior knowledge of elementary data analysis or elementary statistics is assumed.

Prerequisite: Mathematics 13, or permission of the instructor. Dist: QDS.

46. Models of Voting and Decision Making

11W, 12W: Arrange

Is there a fair method of voting to elect a candidate for political office or to apportion representation in Congress among the States? We examine the benefits and problems of traditional plurality voting. Seeking criteria for fairness leads us to Arrow’s axioms for a social welfare function and his ‘impossibility’ theorem. Alternatives to his assumptions are explored as are weighted voting schemes and approval voting, evaluating their advantages and drawbacks. We also explore the concept of fairness in apportionment of congressional districts. Throughout the course both mathematical and political concepts are used to analyze consequences, benefits, and costs.

Prerequisite: By permission only. Government 6 or other introduction to the U.S. political system, and Mathematics 3 or 6 recommended. Dist: QDS. Norman.

80. Seminars in Mathematics and Social Sciences

All terms: Arrange

88. Topics in Mathematics and the Social Sciences

All terms: Arrange

We call attention to the following courses which include some of the more quantitative and mathematical courses in the curriculum of various social science disciplines.

Anthropology 41: Human Evolution


Engineering Sciences 51: Principles of System Dynamics

Engineering Sciences 52: Introduction to Operations Research

Philosophy 27: Philosophy of Science

Psychology 21: Perception

Psychology 28: Cognition

[1] Economics courses are quantitative in nature and the advanced sequential courses quite highly so. Mathematics and Social Science students are encouraged to speak with the professors of the courses that are of substantive interest to the student in order to ascertain whether the mix of quantitative technique and substantive economic issues is right for the student.