Quantitative Reasoning


The aim of courses in this area is to introduce students to mathematical and quantitative modes of thought. Some courses emphasize theoretical aspects of mathematics or statistical reasoning: a course on number theory or deductive logic, for example, would fall under this heading. Other courses in this area explore the application of quantitative methods to questions in the natural sciences, social sciences, or humanities: courses on making decisions under uncertainty, or on analyzing demographic trends are examples of such applications.

Quantitative Reasoning

Quantitative Reasoning 20. Computers and Computing
Catalog Number: 5430 Enrollment: Limited to 60.
William H. Bossert
Half course (spring term). M., W., F., at 9, and a weekly section to be arranged. EXAM GROUP: 2
An algorithm is an unambiguously stated procedure for accomplishing a specific task on the basis of the given information in a given environment. The term is often associated with computer programs. The course will examine a number of algorithms with regard to their design and analysis of their relative efficiency. A central theme is the close interaction between the form of an algorithm and the representation and format of information which it works. Students will learn to design and implement programs of modest complexity in a modern programming language.
Note: Previous programming experience is not required.

Quantitative Reasoning 22. Deductive Logic
Catalog Number: 2508
Richard G. Heck, Jr.
Half course (fall term). M., W., (F.), at 10, and a weekly section to be arranged. EXAM GROUP: 3
The concepts and principles of symbolic logic: valid and invalid arguments, logical relations of statements and their basis in structural features of those statements, the analysis of complex statements of ordinary discourse to uncover their structure, the use of a symbolic language to display logical structure and to facilitate methods for assessing arguments. Analysis of reasoning with truth-functions (“and”, “or”, “not”, “if...then”) and with quantifiers (“all”, “some”). Attention to formal languages and axiomatics, and systems for logical deduction. Throughout, both the theory underlying the norms of valid reasoning and applications to particular problems will be investigated.

[Quantitative Reasoning 24. Health Economics]
Catalog Number: 4667
David M. Cutler
Half course (fall term). Tu., Th., 10–11:30, and a weekly section to be arranged. EXAM GROUP: 12, 13
Analysis of the medical care system is integral to a number of disciplines, including economics, philosophy, sociology, demography, and statistics, as well as four professional schools (medicine, public health, law, and public policy). This course uses quantitative methods to examine the organization and operation of the medical system. The course will cover the medical and non-medical determinants of health; markets for medical care services and health insurance; and proposed reforms of medical care. Methods of analysis will include graphical analysis, algebra, survey design, and use of secondary data. Techniques will be developed in class and section. Use of a computer spreadsheet is required and will be demonstrated in class and section.
Note: Expected to be given in 2001–02.

Quantitative Reasoning 26. Choice and Chance: The Mathematics of Decision Making
Catalog Number: 4123
Daniel L. Goroff and Howard Raiffa (Business School)
Half course (spring term). Tu., Th., 10–11:30, and a weekly section to be arranged. EXAM GROUP: 12, 13
This course develops mathematical ideas that can help individuals make rational choices. We study both decisions whose results are predictable as well as those made under uncertainty, including cases designed for professional school classes. Topics range from methods of optimization to probability theory, and from systems that evolve over time to empirical surprises concerning how people estimate, wager, and make choices in practice.
Note: High school algebra and willingness to think hard are prerequisites.

Quantitative Reasoning 28. The Magic of Numbers
Catalog Number: 4764
Benedict H. Gross and Joseph D. Harris
Half course (fall term). M., W., F., at 10, and a weekly section to be arranged. EXAM GROUP: 3
This course will explore the beauty and mystery of mathematics through a study of the patterns and properties of the natural numbers 1, 2, 3, .... We will discuss various special classes of numbers, like Fibonacci numbers, factorials, and binomials and the many ways they arise in mathematics and in nature. We’ll also investigate the mysterious behavior of prime numbers and their distribution, and discuss coding systems based on modular arithmetic.
Note: We will assume no mathematical background beyond high-school algebra. Emphasis will be placed on discovery through conjecture and experimentation.

[Quantitative Reasoning 30. Quantitative Methods in Political Science]
Catalog Number: 5687
Gary King
Half course (fall term). Hours to be arranged.
This course is about inference in political science: using facts we know to learn about facts we do not know. Its focus is inference from quantitative data (although the same insights apply to good nonquantitative research). Students learn the major quantitative techniques used in political science and related social sciences. The course explores data analysis, as well as descriptive and causal statistical inference of many types. The course emphasizes probability theory, regression analysis and other statistical techniques, and uses techniques of stochastic simulation to get answers easily and to interpret statistical results in a manner very close to the political substance of the problem at hand.
Note: Expected to be given in 2001–02.

Quantitative Reasoning 32. Uncertainty and Statistical Reasoning
Catalog Number: 2228
Carl N. Morris
Half course (fall term). Tu., Th., 10–11:30, and a weekly section to be arranged. EXAM GROUP: 12, 13
Individuals continually must make decisions under uncertainty in their personal and in their professional lives. This course develops probability as the appropriate language for describing uncertainty and it shows how statistical data and planned studies can be crucial when evaluating probabilities and associated risks. It will help students understand and discover how people think about uncertainty and risk. The course will improve each student’s ability to handle uncertainty, and so to make better decisions. It introduces concepts and the language of probability and statistics. Students will review and assess probabilities and statistics developed for and reported in the media, science, industry, law, medicine, and government.
Note: Expected to be omitted in 2001–02.

[Quantitative Reasoning 33. Causal Inference]
Catalog Number: 0424
Donald B. Rubin
Half course (spring term). Hours to be arranged.
Do private schools do a better job than their public counterparts? Does the existence of the QRR improve the quantitative literacy of the undergraduates at Harvard? Such questions dominate many decision-making processes but only rarely are their “answers” based on the careful collection and analysis of empirical data. This courses confronts such questions and how to reach inferentially valid answers that summarize uncertainty using formal probabilistic statements.
Note: Expected to be given in 2001–02.

[Quantitative Reasoning 34. Counting People]
Catalog Number: 4329
Peter T. Ellison
Half course (spring term). M., W., F., at 9, and a weekly section to be arranged. EXAM GROUP: 2
The size, composition, distribution, and dynamics of human populations arise as important variables in many domains of inquiry spanning traditional academic boundaries, including sociology, history, economics, government, public health, and environmental science. This course seeks to introduce students to the field of human demography as both an area of study and a mode of inquiry. Emphasis is placed on understanding the methods by which inferences concerning the nature, distribution, and dynamics of human populations are drawn from census and vital registration data. Students gain experience in the analysis of real demographic data and the application of demographic analyses to a variety of problems drawn from both the social and natural sciences.
Note: Expected to be given in 2001–02.

Quantitative Reasoning 36. Statistics and Public Policy
Catalog Number: 7412
Christopher Winship
Half course (spring term). M., W., F., at 11, and a weekly section to be arranged.
Data, or more accurately statistics calculated from data, are used ubiquitously in the support of various public policy claims. The purpose of this course is to examine the statistical methods used in making such claims and understand their potential strengths and weaknesses. The course examines Sampling, Characteristics of Distributions, Basic Probability, Statistical Reference, Measurement and Scaling, Measures of Association, Experiments, and Quasi-Experiments. The last part of the course will focus on the problem of making causal inferences from empirical data. The goal of the course is to acquire a clear, conceptual understanding of methods as opposed to the ability to manipulate formulas.
Note: Expected to be omitted in 2001–02.

[Quantitative Reasoning 37. Surveys and Statistics in Sociology]
Catalog Number: 8610
Peter V. Marsden
Half course (spring term). Term and Hours to be arranged.
Introduces quantitative analysis in social research, including principles of research design and the use of empirical evidence, particularly from social surveys. Descriptive and inferential statistics, contingency table analysis, and regression analysis. Emphasis on ananlysis of data and presentation of results in research reports.
Note: Expected to be given in 2001–02.

[Quantitative Reasoning 38. The Strategy of International Politics]
Catalog Number: 7119
Half course (spring term). Term and Hours to be arranged.
International politics is often about strategic interaction among states. When governments make choices about economic, military, or environmental policies, they take into account the likely responses and actions of others. This course introduces the logic of strategic interaction by way of game theory. The principles of game theory are introduced, and students learn how to solve simple games. Mathematical topics covered include probabilities, set theory, linear equations, and quadratic equations. The games are motivated and illustrated with examples drawn from international politics. The logic and techniques developed in this class have wide applications outside the field of international relations.
Note: Expected to be given in 2001–02.

Departmental courses that satisfy the Quantitative Reasoning requirement

The following departmental courses may be taken to meet the Quantitative Reasoning requirement. These courses are not necessarily designed for a general audience; they may assume prior experience or more than could be expected of students seeing the subject for the first time.
Computer Science 50. Introduction to Computer Science I
Mathematics 1a. Introduction to Calculus
Mathematics 1b. Calculus, Series and Differential Equations
Mathematics 19. Mathematical Modeling
Mathematics 20. Introduction to Linear Algebra and Multivariable Calculus
Mathematics 21a. Multivariable Calculus
Mathematics 21b. Linear Algebra and Differential Equations
Statistics 100. Introduction to Quantitative Methods
Statistics 101. Introduction to Quantitative Methods
Statistics 102. Fundamentals of Biostatistics
Statistics 104. Introduction to Quantitative Methods
Statistics 110. Introduction to Probability

The following departmental courses taken together may be used to meet the Quantitative Reasoning requirement.

Mathematics Xa. Introduction to Functions and Calculus I
Mathematics Xb. Introduction to Functions and Calculus II