Demographics has become a critical dimension of the work of many journalists, business professionals, and government analysts and managers. Yet those who are not professional demographers often find locating and effectively using demographics difficult. Written by leading authorities, Demographics provides a single-volume resource that is readily understandable by everyone. It describes and demonstrates how students and working professionals can obtain, use, and communicate demographic information effectively. Consisting of ten chapters organized into four sections on basic demographic concepts, definitions, and methods, this book includes sources of demographic and economic data as well as explanations and examples of how to effectively and accurately use them.

The Panel on Estimates of Poverty for Small Geographic Areas was established by the Committee on National Statistics at the National Research Council in response to the Improving America's Schools Act of 1994. That act charged the U.S. Census Bureau to produce updated estimates of poor school-age children every two years for the nation's more than 3,000 counties and 14,000 school districts. The act also charged the panel with determining the appropriateness and reliability of the Bureau's estimates for use in the allocation of more than $7 billion of Title I funds each year for educationally disadvantaged children. The panel's charge was both a major one and one with immovable deadlines. The panel had to evaluate the Census Bureau's work on a very tight schedule in order to meet legal requirements for allocation of Title I funds. As it turned out, the panel produced three interim reports: the first one evaluated county-level estimates of poor school-age children in 1993, the second one assessed a revised set of 1993 county estimates; and the third one covered both county- and school district-level estimates of poor school-age children in 1995. This volume combines and updates these three reports into a single reference volume.

Numerous metallic artefacts, deposited in a hoard in ancient times, came to light by chance on the campus of the Sultan Qaboos University in Al Khawd, Sultanate of Oman. Mostly fashioned from copper, these objects compare well with numerous documented artefact classes from south-eastern Arabia assigned to the Early Iron Age (1200–300 BCE).

A hands-on guide to the use of quantitative methods and software for making successful business decisions The appropriate use of quantitative methods lies at the core of successful decisions made by managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, Data Driven Business Decisions introduces readers to the important role that data plays in understanding business outcomes, addressing four general areas that managers need to know about: data handling and Microsoft Excel®, uncertainty, the relationship between inputs and outputs, and complex decisions with trade-offs and uncertainty. Grounded in the author's own classroom approach to business statistics, the book reveals how to use data to understand the drivers of business outcomes, which in turn allows for data-driven business decisions. A basic, non-mathematical foundation in statistics is provided, outlining for readers the tools needed to link data with business decisions; account for uncertainty in the actions of others and in patterns revealed by data; handle data in Excel®; translate their analysis into simple business terms; and present results in simple tables and charts. The author discusses key data analytic frameworks, such as decision trees and multiple regression, and also explores additional topics, including: Use of the Excel® functions Solver and Goal Seek Partial correlation and auto-correlation Interactions and proportional variation in regression models Seasonal adjustment and what it reveals Basic portfolio theory as an introduction to correlations Chapters are introduced with case studies that integrate simple ideas into the larger business context, and are followed by further details, raw data, and motivating insights. Algebraic notation is used only when necessary, and throughout the book, the author utilizes real-world examples from diverse areas such as market surveys, finance, economics, and business ethics. Excel® add-ins StatproGo and TreePlan are showcased to demonstrate execution of the techniques, and a related website features extensive programming instructions as well as insights, data sets, and solutions to problems included in the material. Data Driven Business Decisions is an excellent book for MBA quantitative analysis courses or undergraduate general statistics courses. It also serves as a valuable reference for practicing MBAs and practitioners in the fields of statistics, business, and finance.