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Statistical Models
This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
eBook
Atlas of sustainable development goals 2017 : from world development indicators
The atlas uses maps, charts and analysis to illustrate, trends, challenges and measurement issues related to each of the 17 Sustainable Development Goals. The Atlas primarily draws on World Development Indicators (WDI) - the World Bank's compilation of internationally comparable statistics about global development and the quality of people's lives Given the breadth and scope of the SDGs, the editors have been selective, emphasizing issues considered important by experts in the World Bank's Global Practices and Cross Cutting Solution Areas. Nevertheless, The Atlas aims to reflect the breadth of the Goals themselves and presents national and regional trends and snapshots of progress towards the UN's seventeen Sustainable Development Goals: poverty, hunger, health, education, gender, water, energy, jobs, infrastructure, inequalities, cities, consumption, climate, oceans, the environment, peace, institutions, and partnerships. Between 1990 and 2013, nearly one billion people were raised out of extreme poverty. Its elimination is now a realistic prospect, although this will require both sustained growth and reduced inequality. Even then, gender inequalities continue to hold back human potential. Undernourishment and stunting have nearly halved since 1990, despite increasing food loss, while the burden of infectious disease has also declined. Access to water has expanded, but progress on sanitation has been slower. For too many people, access to healthcare and education still depends on personal financial means. To date the environmental cost of growth has been high. Accumulated damage to oceanic and terrestrial ecosystems is considerable. But hopeful signs exist: while greenhouse gas emissions are at record levels, so too is renewable energy investment. While physical infrastructure continues to expand, so too does population, so that urban housing and rural access to roads remain a challenge, particularly in Sub-Saharan Africa. Meanwhile the institutional infrastructure of development strengthens, with more reliable government budgeting and foreign direct investment recovering from a post-financial crisis decline. Official development assistance, however, continues to fall short of target levels.
Book
Applied Time Series Econometrics
Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.
eBook
The Penguin atlas of women in the world
\"World events continue to reveal the importance of understanding how women live across continents and cultures. Using maps, text, and other graphics in this new revision of her eye-opening book, Joni Seager employs up-to-the-minute research and data to show what shifts have occurred since the first edition was published over twenty years ago--the strides made by women and the distance still to be traveled. She explores the current status of women in relation to such key issues as: equality, motherhood, feminism, the culture of beauty, women at work, women in the global economy, changing households, domestic violence, girls' welfare, lesbian rights, women in government. Filled with a wealth of information creatively displayed, The Penguin Atlas of Women in the World is an indispensable resource for understanding the world we live in\"--Page 4 of cover.
P_MAP
Probability, random processes, and statistical analysis
Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and Ito process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum-Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and loss networks are treated in detail. The book will be useful to students and researchers in such areas as communications, signal processing, networks, machine learning, bioinformatics, econometrics and mathematical finance. With a solutions manual, lecture slides, supplementary materials and MATLAB programs all available online, it is ideal for classroom teaching as well as a valuable reference for professionals.
eBook
Indigenous statistics : a quantitative research methodology
\"In the first book ever published on Indigenous quantitative methodologies, Maggie Walter and Chris Andersen open up a major new approach to research across the disciplines and applied fields. While qualitative methods have been rigorously critiqued and reformulated, the population statistics relied on by virtually all research on Indigenous peoples continue to be taken for granted as straightforward, transparent numbers. This book dismantles that persistent positivism with a forceful critique, then fills the void with a new paradigm for Indigenous quantitative methods, using concrete examples of research projects from First World Indigenous peoples in the United States, Australia, and Canada. Concise and accessible, it is an ideal supplementary text as well as a core component of the methodological toolkit for anyone conducting Indigenous research or using Indigenous population statistics\"-- Provided by publisher.
Book
A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions
We propose a new bandwidth selection method for kernel estimators of spatial point process intensity functions. The method is based on an optimality criterion motivated by the Campbell formula applied to the reciprocal intensity function. The new method is fully nonparametric, does not require knowledge of higher-order moments, and is not restricted to a specific class of point process. Our approach is computationally straightforward and does not require numerical approximation of integrals.
Journal Article
Robust methods in biostatistics
Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated models as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regression Generalized linear models Linear mixed models Marginal longitudinal data models Cox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.
eBook