By examining some of the basic scaling questions, such as the importance of measurement levels, the kinds of variables needed for Likert or Guttman scales and when to use multidimensional scaling versus factor analysis, Jacoby introduces readers to the most appropriate scaling strategies for different research situations. He also explores data theory, the study of how real world observations can be transformed into something to be analyzed, in order to facilitate more effective use of scaling techniques.

Introduction
Measurement
Data Theory
Dimensionality
Data Theory and Scaling Methods
Alternating Least Squares, Optimal Scaling
Conclusions

William G. Jacoby is a Professor in the Department of Political Science at Michigan State University. He is also a Research Scientist at the University of Michigan, where he serves as Director of the Inter-University Consortium for Political and Social Research (ICPSR) Summer Training Program in Quantitative Methods of Social Research.
Professor Jacoby joined the MSU faculty in 2003. Previously, he held positions at the University of South Carolina, Ohio State University, and the University of Missouri. He received his Ph.D. from the University of North Carolina, Chapel Hill in 1983.
Professor Jacoby¿s main professional interests are mass political behavior (public opinion, political attitudes, voting behavior) and quantitative methodology (measurement theory, scaling methods, statistical graphics, modern regression). His current research focuses on citizen ideology and belief system organization, value choices and their implications for subsequent political orientations, measuring policy priorities in the American states, the implications of measurement assumptions for statistical models, and graphical strategies for data analysis.
Recently, Professor Jacoby has taught courses on public opinion, regression analysis, scaling methods, and statistical graphics.