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The purpose of this book is to introduce, discuss, illustrate, and evaluate the colorful palette of analytical techniques that can be applied to the analysis of household survey data, with an emphasis on the innovations of the past decade or so. Most of the chapters begin by introducing a methodological or policy problem, to motivate the subsequent discussion of relevant methods. They then summarize the relevant techniques, and draw on examples – many of them from the authors’ own work – and aim to convey a sense of the potential, but also the strengths and weaknesses, of those techniques. This book is meant for graduate students in statistics, economics, policy analysis, and social sciences, especially, but certainly not exclusively, those interested in the challenges of economic development in the Third World. Additionally, the book will be useful to academics and practitioners who work closely with survey data. This is a book that can serve as a reference work, to be taken down from the shelf and perused from time to time. Dominique Haughton is Professor of Mathematical Sciences at Bentley University and Affiliated Researcher at Université Toulouse I. Jonathan Haughton is Professor of Economics at Suffolk University and Senior Economist at the Beacon Hill Institute for Public Policy.
Cost and standard of living. --- Cost and standard of living -- Statistical methods. --- Household surveys --- Cost and standard of living --- Economic development --- Business & Economics --- Mathematics --- Physical Sciences & Mathematics --- Labor & Workers' Economics --- Mathematical Statistics --- Demography --- Statistical methods --- Statistical methods. --- Comfort, Standard of --- Cost of living --- Food, Cost of --- Household expenses --- Living, Cost of --- Living, Standard of --- Standard of living --- Statistics. --- Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. --- Statistics for Social Science, Behavioral Science, Education, Public Policy, and Law. --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Consumption (Economics) --- Home economics --- Households --- Quality of life --- Wealth --- Luxury --- Prices --- Purchasing power --- Wages --- Surveys --- Statistics for Social Sciences, Humanities, Law. --- Statistics . --- Developing countries --- Economic conditions --- Emerging nations --- Fourth World --- Global South --- LDC's --- Least developed countries --- Less developed countries --- Newly industrialized countries --- Newly industrializing countries --- NICs (Newly industrialized countries) --- Third World --- Underdeveloped areas --- Underdeveloped countries
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Stochastic processes --- Probabilities --- Probabilités --- Probabilities. --- 519.21 --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Probability theory. Stochastic processes --- 519.21 Probability theory. Stochastic processes --- Probabilités
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The purpose of this book is to introduce, discuss, illustrate, and evaluate the colorful palette of analytical techniques that can be applied to the analysis of household survey data, with an emphasis on the innovations of the past decade or so. Most of the chapters begin by introducing a methodological or policy problem, to motivate the subsequent discussion of relevant methods. They then summarize the relevant techniques, and draw on examples - many of them from the authors' own work - and aim to convey a sense of the potential, but also the strengths and weaknesses, of those techniques. This book is meant for graduate students in statistics, economics, policy analysis, and social sciences, especially, but certainly not exclusively, those interested in the challenges of economic development in the Third World. Additionally, the book will be useful to academics and practitioners who work closely with survey data. This is a book that can serve as a reference work, to be taken down from the shelf and perused from time to time. Dominique Haughton is Professor of Mathematical Sciences at Bentley University and Affiliated Researcher at Université Toulouse I. Jonathan Haughton is Professor of Economics at Suffolk University and Senior Economist at the Beacon Hill Institute for Public Policy.
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Movies will never be the same after you learn how to analyze movie data, including key data mining, text mining and social network analytics concepts. These techniques may then be used in endless other contexts. In the movie application, this topic opens a lively discussion on the current developments in big data from a data science perspective. This book is geared to applied researchers and practitioners and is meant to be practical. The reader will take a hands-on approach, running text mining and social network analyses with software packages covered in the book. These include R, SAS, Knime, Pajek and Gephi. The nitty-gritty of how to build datasets needed for the various analyses will be discussed as well. This includes how to extract suitable Twitter data and create a co-starring network from the IMDB database given memory constraints. The authors also guide the reader through an analysis of movie attendance data via a realistic dataset from France.
Mathematical Statistics --- Mathematics --- Physical Sciences & Mathematics --- Motion pictures --- Visual analytics. --- Philosophy. --- Analytics, Visual --- Statistics. --- Data mining. --- Computer graphics. --- Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. --- Data Mining and Knowledge Discovery. --- Computer Graphics. --- Reasoning --- Information visualization --- Statistics for Social Sciences, Humanities, Law. --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- Computer art --- Graphic arts --- Electronic data processing --- Engineering graphics --- Image processing --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Digital techniques --- Statistics .
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Movies will never be the same after you learn how to analyze movie data, including key data mining, text mining and social network analytics concepts. These techniques may then be used in endless other contexts. In the movie application, this topic opens a lively discussion on the current developments in big data from a data science perspective. This book is geared to applied researchers and practitioners and is meant to be practical. The reader will take a hands-on approach, running text mining and social network analyses with software packages covered in the book. These include R, SAS, Knime, Pajek and Gephi. The nitty-gritty of how to build datasets needed for the various analyses will be discussed as well. This includes how to extract suitable Twitter data and create a co-starring network from the IMDB database given memory constraints. The authors also guide the reader through an analysis of movie attendance data via a realistic dataset from France.
Sociology --- Statistical science --- Law --- Mathematical statistics --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- datamining --- grafische vormgeving --- wetgeving --- statistiek --- data acquisition
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Baulch, Chuyen, Haughton, and Haughton examine the latest quantitative evidence on disparities in living standards between and among different ethnic groups in Vietnam. Using data from the 1998 Vietnam Living Standards Survey and 1999 Census, they show that Kinh and Hoa ("majority") households have substantially higher living standards than "minority" households from Vietnam's other 52 ethnic groups. Subdividing the population into five broad categories, the authors find that while the Kinh, Hoa, Khmer, and Northern Highland minorities have benefited from economic growth in the 1990s, the growth of Central Highland minorities has stagnated. Disaggregating further, they find that the same ethnic groups whose living standards have risen fastest are those that have the highest school enrollment rates, are most likely to intermarry with Kinh partners, and are the least likely to practice a religion. The authors then estimate and decompose a set of expenditure regressions which show that even if minority households had the same endowments as Kinh households, this would close no more than a third of the gap in per capita expenditures. While some ethnic minorities seem to be doing well with a strategy of assimilating (both culturally and economically) with the Kinh-Hoa majority, other groups are attempting to integrate economically while retaining distinct cultural identities. A third group comprising the Central Highland minorities, including the Hmong, is largely being left behind by the growth process. Such diversity in the socioeconomic development experiences of the different ethnic minorities indicates the need for similar diversity in the policy interventions that are designed to assist them. This paper-a product of Macroeconomics and Growth, Development Research Group-is part of a larger effort in the group to study household welfare and poverty reduction in Vietnam. Jonathan Haughton may be contacted at jhaughto@beaconhill.org.
Adoption --- Anthropology --- Communities & Human Settlements --- Culture & Development --- Disability --- Economic Growth --- Education --- Education for All --- Ethnic Groups --- Fertility --- Fertility Rate --- Gender --- Gender and Education --- Health, Nutrition and Population --- Housing and Human Habitats --- Human Capital --- Living Standards --- Minority --- Policy --- Population --- Population Policies --- Populations --- Poverty --- Poverty Reduction --- Primary Education --- Rural Development --- Rural Poverty --- Rural Poverty Reduction --- School Enrolment --- Small Area Estimation Poverty Mapping --- Social Protections and Labor --- Socioeconomic Development --- Socioeconomic Differences --- Urban Areas --- Women --- Workshop --- Young Children
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