Presenting an introduction to computing and advice on computer applications, this book examines hardware and software with respect to the needs of the social scientist. It offers a framework for the use of computers, with focus on the 'work station', the center of which is a personal computer connected to networks by a telephone-based modem.

This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.

Do your students lack confidence in their ability to handle quantitative work? Do they get confused about how to enter statistical data on SAS, SPSS, and Excel programs? The new Third Edition of the bestselling Statistics for the Social Sciences is the solution to these dilemmas Popular in previous editions, this Third Edition continues to help build students' confidence and ability in doing statistical analysis by slowly moving from concepts that require little computational work to those that require more. Author R. Mark Sirkin once again demonstrates how statistics can be used so that students come to appreciate their usefulness rather than fearing them. Statistics for the Social Sciences emphasizes the analysis and interpretation of data to give students a feel for how data interpretation is related to the methods by which the information was obtained. The book includes lists of key concepts, chapter exercises, topic boxes, and more

The Institute of Food Technologists (IFT) recently endorsed the use of computers in food science education. The minimum standards for degrees in food science, as suggested by IFT,"require the students to use computers in the solution of problems, the collection and analysis of data, the control processes, in addition to word processing."Because they are widely used in business, allow statistical and graphical of experimental data, and can mimic laboratory experimentation, spreadsheets provide an ideal tool for learning the important features of computers and programming. In addition, they are ideally suited for food science students, who usually do not have an extensive mathematical background.Drawing from the many courses he has taught at UC Davis, Dr. Singh covers the general basics of spreadsheets using examples specific to food science. He includes more than 50 solved problems drawn from key areas of food science, namely food microbiology, food chemistry, sensory evaluation, statistical quality control, and food engineering. Each problem is presented with the required equations and detailed steps necessary for programming the spreadsheet. Helpful hints in using the spreadsheets are also provided throughout the text.Key Features* The first book to integrate speadsheets in teaching food science and technology* Includes more than 50 solved examples of spreadsheet use in food science and engineering* Presents a step-by-step introduction to spreadsheet use* Provides a food composition database on a computer disk

This second edition has been completely updated to include new studies, new computer applications and an additional chapter on problems and issues that can arise when carrying out content analysis in four major categories: measurement, indication, representation and interpretation.

Tools of data comparison and analysis are critical in the field of archaeology, and the integration of technological advancements such as geographic information systems, intelligent systems, and virtual reality reconstructions with the teaching of archaeology is crucial to the effective utilization of resources in the field. E-Learning Methodologies and Computer Applications in Archaeology presents innovative instructional approaches for archaeological e-learning based on networked technologies, providing researchers, scholars, and professionals a comprehensive global perspective on the resources, development, application, and implications of information communication technology in multimedia-based educational products and services in archaeology.

Document from the year 2012 in the subject Communications - Methods and Research Logic, Kampala International University, course: undergraduates and graduates, language: English, abstract: Researches fundamentals are of great importance in disciplines and interested people on searching various knowledge or solution to a phenomenon. The main purpose of the book is to share scholarly knowledge about research and its complexity. This book can be used to train the basics and techniques involved on doing inquiries from different views. The experience shows that, no one single cure for all diseases. So when comes to research, there is no single research methodology or technique which fits all circumstances. Hence, the book tries to identify a family of approaches towards various research situations and distinguish their outcomes. Thus, various disciplines example human resource management, accounts and project management have different environmental set up i.e. matters in question, study elements involved and the study plan can determine research context. The study consulted scholars in different disciplines through their publications that explain various research methodologies. Generally the books highlighted some technical guide lines on conducting researches and report writing which provide overview on research plans. In chapter one, the book tried to explain how to choose among the methods of inquiries. It includes the meaning of research, research approaches and types. Chapter two addressing the types of variables deployed in a study. Either, chapter three tells how to generate research idea. Rather, the book through chapter four described how to develop a re-searchable topics. Meanwhile chapter five gives explanation on how to carry out literature survey that forms a crucial party of studies. Then chapter six is critically explain research designs and research management. The book concludes with the application of computer software in research process. Therefore, the book intended to guide researchers, academician and groom young researchers to conduct different inquiries. This is due to the fact that, human activities and environmental changes created complexity in life as well as challenges. So far; challenges need answers from fundamental questions such as what, where, who and how. It is the main reason for interested groups such as researchers, academician and practitioners to seek guidance during research. This is done to attain answers towards fundamental questions.

This combinatorics text provides in-depth coverage of recurrences, generating functions, partitions, and permutations, along with some of the most interesting graph and network topics, design constructions, and finite geometries. It presents the computer and software algorithms in pseudo-code and incorporates definitions, theorems, proofs, examples, and nearly 300 illustrations as pedagogical elements of the exposition. Numerous problems, solutions, and hints reinforce basic skills and assist with creative problem solving. The author also offers a website with extensive graph theory informational resources as well as a computational engine to help with calculations for some of the exercises.

Ontology was once understood to be the philosophical inquiry into the structure of reality: the analysis and categorization of ‘what there is’. Recently, however, a field called ‘ontology’ has become part of the rapidly growing research industry in information technology. The two fields have more in common than just their name. Theory and Applications of Ontology is a two-volume anthology that aims to further an informed discussion about the relationship between ontology in philosophy and ontology in information technology. It fills an important lacuna in cutting-edge research on ontology in both fields, supplying stage-setting overview articles on history and method, presenting directions of current research in either field, and highlighting areas of productive interdisciplinary contact. Theory and Applications of Ontology: Computer Applications presents ontology in ways that philosophers are not likely to find elsewhere. The volume offers an overview of current research in ontology, distinguishing basic conceptual issues, domain applications, general frameworks, and mathematical formalisms. It introduces the reader to current research on frameworks and applications in information technology in ways that are sure to invite reflection and constructive responses from ontologists in philosophy.

Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.