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Handbook of Statistical Data Editing and Imputation
A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible...
Artificial Intelligence and Machine Learning
This book contains a selection of the best papers of the 32nd Benelux Conference on Artificial Intelligence, BNAIC/Benelearn 2020, held in Leiden, The Netherlands, in November 2020. Due to the COVID-19 pandemic the conference was held online. The 12 papers presented in this volume were carefully reviewed and selected from 41 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis. The chapter 11 is published open access under a CC BY license (Creative Commons Attribution 4.0 International License) Chapter “Gaining Insight into Determinants of Physical Activity Using Bayesian Network Learning” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..
A Passion for Passion
A Passion for Passion is a love letter to genre romance fiction. It celebrates the joyful silliness of books that are written to follow the rules. Alice Fraser has a special place in her heart for the sweeping silliness of romance novels. The journey to reach a believable Happily Ever After can go via an unbelievable rollercoaster of intensity, through wildly entertaining twists and unlikely turns. To celebrate the unparalleled joy this genre can bring to readers and defy its oft maligned status, Alice has created the author, D'Ancey LaGuarde, the ineffably mysterious, outrageously prolific, undisputed regent of the art of romance. Collecting together excerpts, book cover designs, character ...
Working with Data in Public Health: A Practical Pathway with R
This book provides a complete practical guide of processing data in public health with R language. On the basis of the author’s research and teaching experiences, this book serves either as a textbook for undergraduates and graduates in public health or as a tutorial for self-learning. Many first-hand examples are presented with source data, R scripts, and graphs, as well as detailed explanations, which could be easily reproduced by readers so as to better understand the data processing principles and procedures. Popular and novel R packages in public health are introduced as well.
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:...
Statistical Data Cleaning with Applications in R
A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: Focuses on the automation of data cleaning methods, including both theory and applications written in R. Enables the reader to design ...
Quantitative Methoden in der Politikwissenschaft
Dieses Lehrbuch bietet eine Einführung in die sozialwissenschaftliche Forschungslogik und den quantitativen Forschungsprozess. Die einzelnen Phasen des Forschungsprozesses – Forschungsthema und Entwicklung einer Forschungsfrage, Konzeptspezifikation, Hypothesenbildung, Operationalisierung, Forschungsdesign, Auswahlverfahren und Datenerhebung – werden anhand politikwissenschaftlicher Beispiele dargestellt und erläutert. Zudem werden wichtige sozialwissenschaftliche Datensätze vorgestellt und die Bedeutung der Sekundäranalyse herausgearbeitet. Das Buch bietet damit zentrale Informationen, die für ein Verständnis der quantitativen Sozialforschung und die Auseinandersetzung mit empirischen Studien erforderlich sind.
Handbuch Empirische Organisationsforschung
Das Handbuch gibt einen Überblick über zentrale Methoden der empirischen Organisationsforschung. Ein Schwerpunkt liegt auf den Analysepotenzialen existierender Datenbestände und den Anwendungsfeldern quantitativer sowie qualitativer Erhebungsmethoden in der Organisationsforschung. Durch die Berücksichtigung der methodischen und forschungspraktischen Herausforderungen bei verschiedenen Organisationstypen – z.B. Hochschulen, Krankenhäuser, Unternehmen, Verwaltungen und Parteien – vermittelt das Handbuch ein breites, mit Erfahrungen aus der Praxis der empirischen Organisationsforschung unterfüttertes Methodenwissen.
Big Data and Social Science
Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
Correction of Rounding, Typing, and Sign Errors with the Deducorrect Package
Since raw (survey) data usually has to be edited before statistical analysis can take place, the availability of data cleaning algorithms is important to many statisticians. In this paper the implementation of three data correction methods in R are described. The methods of this package can be used to correct numerical data under linear restrictions for typing errors, rounding errors, sign errors and value interchanges. The algorithms, based on earlier work of Scholtus, are described and implementation details with coded examples are given. Although the algorithms have originally been developed with financial balance accounts in mind the algorithms are formulated generically and can be applied in a wider range of applications.
