A wonderfully written and entertaining book which places Britain under the microscope and asks who we are today and how we've changed as a nation. 'Entertaining and absorbing' - The Sunday Times In 1841 there were 734 female midwives working in Britain, along with 9 artificial eye makers, 20 peg makers, 6 stamp makers and 1 bee dealer. Fast forward nearly two centuries and there are 51,000 midwives working in the UK and not an eye maker in sight! For the past two centuries, the National Census has been monitoring the behaviour of the British: our work-lives, homes lives and strange cultural habits. With questions on occupation, housing, religion, travel and family, the Census is a snapshot of a country at any given epoch, and its findings have informed the economy, politics and every other national matter for decades that followed. Now, for the first time ever, the Census findings of the past two centuries are collected in to a wonderfully written and entertaining book which places Britain under the microscope and asks who we are and how we've changed as a nation. On our occupations, our working lives, relationships; our quirks, habits, weird interests and cultural beliefs - this book takes the reader on a journey through the statistical findings of one of the most valuable pieces of ongoing historical research of modern times, and asks us what these fascinating numbers tells us about the Britain in the 21st century.

Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.

This user manual describes in detail the National Statistics Socio-Economic Classification (NS-SEC), the standard UK government classification, which was rebased following changes to the Standard Occupation Classification (SOC) in 2000, and gives practical advice on using it to derive classifications. The main chapters describe the classes and general principles for deriving classifications and the appendices contain detailed derivation tables explaining how each category is derived from SOC and employment status.

ONS Productivity Handbook: a Statistical Overview and Guide examines the importance and relevance of economic productivity and serves as a reference on the subject. Areas covered include productivity analysis within various sectors and at firm level as well as measures of labour and capital inputs.

This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.

This book introduces researchers to all aspects of the new classification. In particular, it: - Fully describes the NS-SEC and elucidates its conceptual basis - Guides readers in how the NS-SEC has been validated as a measure - Evaluates how well NS-SEC works in describing and explaining the relationships between social class and key health and employment variables - Demonstrates the applications of NS-SEC in research