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Author: Daniel S. Hamermesh Publisher: Elsevier Science Limited ISBN: 9780444515346 Category : Business & Economics Languages : en Pages : 372
Book Description
These studies are based on information on time use in nine countries. It deals with the "when?" and "with whom?" questions describing human behavior, "what is done?" questions of the quantities and determinants of economic activities as well as children's issues and issues involved in the creation of the American Time Use Survey (ATUS).
Author: Daniel S. Hamermesh Publisher: Elsevier Science Limited ISBN: 9780444515346 Category : Business & Economics Languages : en Pages : 372
Book Description
These studies are based on information on time use in nine countries. It deals with the "when?" and "with whom?" questions describing human behavior, "what is done?" questions of the quantities and determinants of economic activities as well as children's issues and issues involved in the creation of the American Time Use Survey (ATUS).
Author: I. Gusti Ngurah Agung Publisher: John Wiley & Sons ISBN: 1118176308 Category : Mathematics Languages : en Pages : 502
Book Description
Do you want to recognize the most suitable models for analysis of statistical data sets? This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometric models for time series data. The procedures introduced are easily extendible to cross-section data sets. The author: Provides step-by-step directions on how to apply EViews software to time series data analysis Offers guidance on how to develop and evaluate alternative empirical models, permitting the most appropriate to be selected without the need for computational formulae Examines a variety of times series models, including continuous growth, discontinuous growth, seemingly causal, regression, ARCH, and GARCH as well as a general form of nonlinear time series and nonparametric models Gives over 250 illustrative examples and notes based on the author's own empirical findings, allowing the advantages and limitations of each model to be understood Describes the theory behind the models in comprehensive appendices Provides supplementary information and data sets An essential tool for advanced undergraduate and graduate students taking finance or econometrics courses. Statistics, life sciences, and social science students, as well as applied researchers, will also find this book an invaluable resource.
Author: Wendy E. Pentland Publisher: Springer Science & Business Media ISBN: 0306459515 Category : Social Science Languages : en Pages : 290
Book Description
This collection demonstrates the use and variety of applications of time use methodology from multidisciplinary, multinational, and multicultural perspectives. A distinguished roster of contributors from such fields as psychology, occupational therapy, sociology, economics, and architecture examines the complex relationship between human time utilization and health and well-being and evaluates the future of time use analysis as a research tool in the social sciences.
Author: Christina A. Russell Publisher: IAP ISBN: 1648022553 Category : Education Languages : en Pages : 357
Book Description
Measure, Use, Improve! Data Use in Out-of-School Time shares the experience and wisdom from a broad cross-section of out-of-school time professionals, ranging from internal evaluators, to funders, to researchers, to policy advocates. Key themes of the volume include building support for learning and evaluation within out-of-school time programs, creating and sustaining continuous quality improvement efforts, authentically engaging young people and caregivers in evaluation, and securing funder support for learning and evaluation. This volume will be particularly useful to leadership-level staff in out-of-school time organizations that are thinking about deepening their own learning and evaluation systems, yet aren’t sure where to start. Authors share conceptual frameworks that have helped inform their thinking, walk through practical examples of how they use data in out-of-school time, and offer advice to colleagues.
Author: Wendy E. Pentland Publisher: Springer Science & Business Media ISBN: 0306471558 Category : Social Science Languages : en Pages : 290
Book Description
This collection demonstrates the use and variety of applications of time use methodology from multidisciplinary, multinational, and multicultural perspectives. A distinguished roster of contributors from such fields as psychology, occupational therapy, sociology, economics, and architecture examines the complex relationship between human time utilization and health and well-being and evaluates the future of time use analysis as a research tool in the social sciences.
Author: Boris Sobolev Publisher: Springer Science & Business Media ISBN: 0387764224 Category : Medical Languages : en Pages : 221
Book Description
Why some patients wait longer than others remains an important question. This book is a reference for health services researchers looking for statistical tools with which to study waiting times. The book offers detailed coverage of statistical concepts and methods for the analysis and interpretation of waiting-time data. It provides analysis from health services research perspective, rather than operations management, and contains a collection of examples.
Author: Katharine G. Abraham Publisher: University of Chicago Press ISBN: 022680125X Category : Business & Economics Languages : en Pages : 502
Book Description
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.
Author: National Research Council Publisher: National Academies Press ISBN: 0309287812 Category : Mathematics Languages : en Pages : 191
Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author: Charles D. Kirkpatrick Publisher: FT Press ISBN: 0132931931 Category : Business & Economics Languages : en Pages : 209
Book Description
In Time the Markets, award-winning technical analyst Charles D. Kirkpatrick applies technical analysis to key economic indicators and shows how to use them to identify market shifts, avoid loss, and become a more profitable long-term investor. Drawing on many years of publicly available data, Kirkpatrick demonstrates how to uncover powerful buy and sell signals and shows how to incorporate corporate, industry, monetary, sentiment, and market data into reliable timing indicators that can help you recognize impending stock and bond market dangers--and get out of the way. Relying primarily on proven technical analysis methods, Kirkpatrick incorporates trading system methods that have proven successful in market timing, including trend and momentum analysis, use of protective and trailing stops, and periodicity. Reflecting the latest insights into behavioral finance, he shares important new insight into measuring marketplace momentum and sentiment--helping long-term investors identify and evade the marketplace irrationalities that often cause capital loss.
Author: Daniel S. Hamermesh
Author: Daniel S. Hamermesh
Author: I. Gusti Ngurah Agung
Author: Wendy E. Pentland
Author: Andrew Harvey
Author: Christina A. Russell
Author: Wendy E. Pentland
Author: Boris Sobolev
Author: Katharine G. Abraham
Author: National Research Council
Author: Charles D. Kirkpatrick