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.

This volume discusses an important area of statistics and highlights the most important statistical advances. It is divided into four sections: statistics in the life and medical sciences, business and social science, the physical sciences and engineering, and theory and methods of statistics.

Deals with official statistics produced by the federal government to meet decision-making needs in the various social and economic sectors.

This volume discusses an important area of statistics and highlights the most important statistical advances. It is divided into four sections: statistics in the life and medical sciences, business and social science, the physical sciences and engineering, and theory and methods of statistics.

This work, which provides a guide for revising and expanding statistical and quantitative methods pedagogy, is useful for novice and seasoned instructors at both undergraduate and graduate levels, inspiring them to use transformative approaches to train students as future researchers. Is it time for a radical revision in our pedagogical orientation? How are we currently teaching introductory statistics and quantitative methods, and how should we teach them? What innovations are used, what is in development? This ground-breaking edited volume addresses these questions and more, providing cutting-edge guidance from highly accomplished teachers. Many current textbooks and syllabi differ in only superficial ways from those used 50 years ago, yet the field of quantitative methods--and its relationship to the research enterprise--has expanded in many important ways. A philosophical axiom underlying this book is that introductory teaching should prepare students to potentially enter more advanced quantitative methods training and ultimately to become accomplished researchers. The reader is introduced to classroom innovation, and to both pragmatic and philosophical challenges to the status quo, motivating a broad revolution in how introductory statistics and quantitative methods are taught. Designed to update and renovate statistical pedagogy, this material will stimulate students, new instructors, and experienced teachers.

The Committee on National Statistics (CNSTAT) convened a workshop on November 4-5, 1999, to identify new directions for health statistics and the implications for health data of changes in the health arena faced by DHHS; state and local health departments; the consumers, developers, and providers of health care products and services; and other health policy makers. Changes in our understanding of health, in health care (managed care, Medicaid, Medicare), in welfare reform, in federal-state relations, in the availability of administrative data, in advanced genetic data, in information technology, in confidentiality issues, and in data integration are examples of recent developments that may play a significant role for DHHS in making future policy decisions.

A selection of articles presented at the Eighth Lukacs Symposium held at the Bowling Green State University, Ohio. They discuss consistency and accuracy of the sequential bootstrap, hypothesis testing, geometry in multivariate analysis, the classical extreme value model, the analysis of cross-classified data, diffusion models for neural activity, e