Introduces students to the basic tools in using data to make informed management decisions. Covers introductory probability, decision analysis, basic statistics, regression, simulation, and linear and nonlinear optimization. Computer spreadsheet exercises and examples drawn from marketing, finance, operations management, and other management functions. Restricted to Sloan Fellows.
Students investigate the difference between qualitative and quantitative measurements and observations. By describing objects both qualitatively and quantitatively, students learn that both types of information are required for complete descriptions. Students discuss various the characteristics of many objects, demonstrating how engineers use both qualitative and quantitative information in product design.
Subject:
Mathematics and Statistics, Science and Technology
Introduction to "soft" consumer research methods, useful for getting quick customer input into decisions on product design and development, strategic positioning, advertising, and branding. Covers interview techniques, observational methods, Voice of the Customer, focus groups, and analyses suitable for qualitative data. Introduces new information-gathering methods in development at MIT.
Students expand upon their understanding of simple machines with an introduction to compound machines. A compound machine a combination of two or more simple machines can affect work more than its individual components. Engineers who design compound machines aim to benefit society by lessening the amount of work that people exert for even common household tasks. This lesson encourages students to critically think about machine inventions and their role in our lives.
Subject:
Mathematics and Statistics, Science and Technology
Introduction to the QFT control method. QFT stands for Quantitative Feedback Theory, which emphasizes the use of feedback in order to achieve adequate robust system performance tolerances despite the presence of plant and disturbances uncertainties.
This module presents students with a number of problems related to statistical sampling and data. In particular, students are asked to demonstrate understanding of concepts such as frequency, relative frequency, and cumulative relative frequency, random samples, quantitative vs. qualitative data, continuous vs. discrete data, and other key terms related to sampling and data. The module is based on the module Sampling and Data: Homework from the textbook collection Collaborative Statistics by Susan Dean and Dr. Barbara Illowsky; additional problems have been added to the original module.
This module introduces the concepts of qualitative data, quantitative continuous data, and quantitative discrete data as used in statistics. Sample problems are included.
A project subject that teaches students how to create, carry out, interpret, and analyze a market research questionnaire. Emphasis on discovering market structure and segmentation, but students can pursue other project applications. Includes a user-oriented treatment of multivariate analysis (factor analysis, multidimensional scaling, conjoint and cluster analysis).
This graduate seminar introduces an emerging research program within International Relations on territorial conflict. While scholars have recognized that territory has been one of the most frequent issues over which states go to war, territorial conflicts have only recently become the subject of systematic study. This course will examine why territorial conflicts arise in the first place, why some of these conflicts escalate to high levels of violence and why other territorial disputes reach settlement, thereby reducing the likelihood of war. Readings in the course draw upon political geography and history as well as qualitative and quantitative approaches to political science.
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