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In this paper we discuss some issues which arise when applying classical data analysis techniques to interval data, focusing on the notions of dispersion, association and linear combinations of interval variables. We present some methods that have been proposed for analysing this kind of data, namely for clustering, discriminant analysis, linear regression and interval time series analysis.

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The evaluation of the urban quality of life has been an important aspect of the research concerning the contemporary city and an increasingly support to urban planning and management. As part of a project to monitor the quality of life in the city of Porto, a survey of the resident population was conducted in order to study the citizens' perceptions of their local quality of life and its evolution in recent years. The opinions of individuals on their level of satisfaction with various fields of the urban quality of life are systematised, as well as their integrated assessment. This analysis is complemented by a multivariate analysis that allows the grouping of the interviewees in large homogenous groups and their social and economic characterisation. Based on the results achieved, we try to highlight the usefulness of the qualitative analysis of the quality of life to support the definition of urban policies. © 2007 Springer Science + Business Media BV/The International Society for Quality-of-Life Studies (ISQOLS).

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This chapter introduces the volume on Applications of Data Mining in E-Business and Finance. It discusses how application-specific issues can affect the development of a data mining project. An overview of the chapters in the book is then given to guide the reader.

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