Provides a method and workflow, based on Benford's Law, for assessing the validity of self-reported social science data.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Michael A. Long is a Professor of Sociology at Oklahoma State University, USA. He is the author or co-author of six books and over 90 journal articles and book chapters primarily in the areas of environmental sociology, green criminology, sustainability, food insecurity, public health, and quantitative methodology. He has received funding from the National Science Foundation, US Department of Agriculture, the British Academy, among others for his research.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Artikel-Nr. ria9781009124249_new
Anzahl: Mehr als 20 verfügbar
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. 2023. paperback. . . . . . Books ship from the US and Ireland. Artikel-Nr. V9781009124249
Anzahl: Mehr als 20 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Benford's Law is a probability distribution for the likelihood of the leading digit in a set of numbers. This book seeks to improve and systematize the use of Benford's Law in the social sciences to assess the validity of self-reported data. The authors first introduce a new measure of conformity to the Benford distribution that is created using permutation statistical methods and employs the concept of statistical agreement. In a switch from a typical Benford application, this book moves away from using Benford's Law to test whether the data conform to the Benford distribution, to using it to draw conclusions about the validity of the data. The concept of 'Benford validity' is developed, which indicates whether a dataset is valid based on comparisons with the Benford distribution and, in relation to this, diagnostic procedure that assesses the impact of not having Benford validity on data analysis is devised. Artikel-Nr. 9781009124249
Anzahl: 1 verfügbar