Daniel T. O'Brien (School of Public Policy and North Urban Affairs

Urban Informatics

Using Big Data to Understand and Serve Communities

• Broschiertes Buch

Produktbeschreibung

This book introduces the reader to the tools of data management, analysis, and manipulation using R statistical software. Designed for undergraduate and above level courses, this book is an ideal onramp for the study of urban informatics and how to translate novel data sets into new insights and practical tools.

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Produktdetails

• Chapman & Hall/CRC Data Science Series
• Verlag: Taylor & Francis Ltd
• Seitenzahl: 340
• Erscheinungstermin: 8. Dezember 2022
• Englisch
• Abmessung: 255mm x 176mm x 24mm
• Gewicht: 682g
• ISBN-13: 9781032264592
• ISBN-10: 1032264594
• Artikelnr.: 64667131

Autorenporträt

Daniel T. O'Brien is Associate Professor in the School of Public Policy and Urban Affairs and the School of Criminology and Criminal Justice at Northeastern University. He focuses on the use of modern digital data sets to better understand urban processes, including crime, education, transportation, public health, and neighborhood social dynamics. He is Director of the Boston Area Research Initiative, in which capacity he has worked extensively to build effective models of research-policy collaboration that help us to better understand and serve cities. His previous book, The Urban Commons, captures the intersection of his efforts to advance both science and practice in cities, using the study of "custodianship" in neighborhoods through Boston's 311 system to illustrate the potential of cross-sector collaborations in urban informatics.

Inhaltsangabe

1 Introduction 2 Welcome to R 3 Telling a Data Story: Examining Individual
Records 4 The Pulse of the City: Observing Variable Patterns 5 Uncovering
Information: Making and Creating Variables 6 Measuring with Big Data 7
Making Measures from Records: Aggregating and Merging Data 8 Mapping
Communities 9 Advanced Visual Techniques 10 Beyond Measurement: Inferential
Statistics (and Correlations) 11 Identifying Inequities across Groups:
ANOVA and t-Test 12 Unpacking Mechanisms Driving Inequities: Multivariate
Regression 13 Advanced Analytic Techniques 14 Emergent Technologies