Quantitative Reasoning 22. Deductive Logic
Catalog Number: 2508
Warren Goldfarb
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.
Note: Expected to be omitted in 2000–01.
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.
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, bet and choose 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, Catalan 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 alternative counting systems such as 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 2000–01.
Quantitative Reasoning 32. Uncertainty and Statistical Reasoning
Catalog Number: 2228
Carl N. Morris
Half course (fall term). Tu., Th., 8:30–10, and a weekly section to be arranged. EXAM GROUP: 10, 11
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 2000–01.
[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 2000–01.