Advances In Business Statistics Methods And Data Collection

ADVANCES IN BUSINESS STATISTICS, METHODS AND DATA COLLECTION Advances in Business Statistics, Methods and Data Collection delivers insights into the latest state of play in producing establishment statistics, obtained from businesses, farms and institutions. Presenting materials and reflecting discussions from the 6th International Conference on Establishment Statistics (ICES-VI), this edited volume provides a broad overview of methodology underlying current establishment statistics from every aspect of the production life cycle while spotlighting innovative and impactful advancements in the development, conduct, and evaluation of modern establishment statistics programs. Highlights include: Practical discussions on agile, timely, and accurate measurement of rapidly evolving economic phenomena such as globalization, new computer technologies, and the informal sector. Comprehensive explorations of administrative and new data sources and technologies, covering big (organic) data sources and methods for data integration, linking, machine learning and visualization. Detailed compilations of statistical programs’ responses to wide-ranging data collection and production challenges, among others caused by the Covid-19 pandemic. In-depth examinations of business survey questionnaire design, computerization, pretesting methods, experimentation, and paradata. Methodical presentations of conventional and emerging procedures in survey statistics techniques for establishment statistics, encompassing probability sampling designs and sample coordination, non-probability sampling, missing data treatments, small area estimation and Bayesian methods. Providing a broad overview of most up-to-date science, this book challenges the status quo and prepares researchers for current and future challenges in establishment statistics and methods. Perfect for survey researchers, government statisticians, National Bank employees, economists, and undergraduate and graduate students in survey research and economics, Advances in Business Statistics, Methods and Data Collection will also earn a place in the toolkit of researchers working –with data– in industries across a variety of fields.

This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.

The Book Advanced Business Statistics Has Attempted To Achieve Two Objectives, That Is, To Make The Subject Matter Very Clear And Understandable To The Students And To Put The Collection Of Numerical Problems In A Systematic Manner At One Place. It Will Fully Meet The Needs Of The Students Of Various Examinations Like M.Com., D.C.M.A., I.C.W.A., C.A., M.B.A., Etc.

Empowering management students with statistical decision-making skills, this text instructs on how to become active participants where statistical findings are reported. Descriptions are provided of the vast role that statistics play in fields such as marketing, finance, human resources, production, and logistics. Rather than being a passive observer, this guide educates the meaning behind the numbers that allow those in business situations to be informed members of the decision-making process.

Applied Business Statistics 5e is an introductory and intermediate Statistics text for students of Management. Its business applications-oriented approach aims to teach Management students how statistics (or data analytics) can be used as a valuable decision-support tool in any discipline of management practice.

Applied Business Statistics: Methods and Excel-basedapplications (second edition) is an introductory Statistics text written specifically for Management students who require an understanding of the role of Statistics in analysing business data in fields such as Marketing, Finance, Human Resources, Production and Logistics. The primary focus of this text is to empower management students with statistical decision making skills so that they become active participants rather than passive observers in business situations where statistical findings are reported and discussed as part of a management decision making process. The text is divided into three major sections: „h exploratory data analysis „h statistical inferences, and „h statistical modelling. Each section focuses on a different role of Statistics as a decision support tool. Emphasis is therefore placed on: „h the data requirements for the various techniques and issues of data quality „h indentifying likely application areas through numerous illustrative examples „h noting the limitations of techniques for decision analysis, and the valid management interpretation of statistical findings. A new feature of this edition of Applied Business Statistics is the use of computer software such as Excel to perform statistical analysis. Excel¡¦s statistical capabilities are illustrated through numerous worked examples found in the text. Students are given the opportunity to familiarize themselves with Excel¡¦s statistical capabilities by applying them to data sets of business problems, which are available on the accompanying CD. Students can monitor their learning with the help of the exercises at the end of every chapter. Each statistical technique is developed through business-related worked examples drawn from the author¡¦s diverse work experiences as a statistical consultant. In this way, a student can readily grasp the basic concept of the technique as well as see how it would be applied in practice. This combination of method and application should prove helpful to both student and lecturer. With a working knowledge of Excel, students can become managers who are able to design and conduct their own statistical analysis in the workplace. Applied Business Statistics is therefore accessible to all students, as only a basic level of mathematical ability is required to work through this book.

This volume brings together a selection of papers presented at the 2017 European Establishment Statistics Workshop, which have been revised and expanded here. Several contributions will serve to deepen the reader’s understanding of the unit problem in business statistics, while further chapters showcase recent advances in business survey methodology and practice in areas such as linking and data integration, sampling and estimation, data collection from businesses, measurement and mitigation of response burden in business surveys, among others. Written by leading experts in business statistics, the volume offers detailed and up-to-date findings to survey methodologists and practitioners working with business statistics. It will also be useful for readers in official statistics, academia and the private sector.

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.

This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry. These include applications from a range of industries that include micro-electronics, chemical, automotive, engineering, food, component assembly, household goods and plastics. Methods range from basic graphical approaches to generalised modelling, from designed experiments to process control. Solutions cover produce and process design, through manufacture to packaging and delivery, from single responses to multivariate problems.