WordStat
WordStat can be used by anyone who needs to quickly extract and analyze information from large amounts of documents. Our content analysis and text mining software is used for:
• Content analysis of open-ended responses, interview or focus group transcripts
• Business intelligence and competitive websites analysis
• Information extraction and knowledge discovery from incident reports, customer complaints
• Content analysis of news coverage or scientific literature
• Automatic tagging and classification of documents
• Fraud detection, authorship attribution, patent analysis
• Taxonomy development and validation
- Video TutorialsLinks to tutorials and short demonstration videos that will help you familiarize yourself with the basics plus some of the advanced features.
WordStat tutorial videos are listed below the QDA Miner tutorial videos.
DataMiner (QDA Miner)
- DataMinerQDA Miner qualitative data analysis software can be used by anyone who needs to code text or pictures, annotate, search, explore and extract information from small or large collections of documents and images, including:
• Researchers in social sciences, medicine, and psychology
• Sociologists, political scientists and ethnographers
• Business intelligence analysts, market researchers, pollsters, and CRM professionals
• Crime analysts, fraud detection experts, lawyers, and paralegal professionals
• Journalists, historians and research assistants
• Document management specialists and librarians - Video TutorialsLinks to tutorials and short demonstration videos that will help you familiarize yourself with the basics plus some of the advanced features.
SPSS
- SPSSThe IBM SPSS® software platform offers advanced statistical analysis, a vast library of machine-learning algorithms, text analysis, open-source extensibility, integration with big data and seamless deployment into applications.
A selection of eBooks
Analysis and visualization of citation networks by
Citation analysis--the exploration of reference patterns in the scholarly and scientific literature-- has long been applied in a number of social sciences to study research impact, knowledge flows, and knowledge networks. It has important information science applications as well, particularly in knowledge representation and in information retrieval. Recent years have seen a burgeoning interest in citation analysis to help address research, management, or information service issues such as university rankings, research evaluation, or knowledge domain visualization. This renewed and growing interest stems from significant improvements in the availability and accessibility of digital bibliographic data (both citation and full text) and of relevant computer technologies. The former provides large amounts of data and the latter the necessary tools for researchers to conduct new types of large-scale citation analysis, even without special access to special data collections. Exciting new developments are emerging this way in many aspects of citation analysis.
Biostatistics : the bare essentials by
This new edition of Biostatistics: The Bare Essentials continues the tradition of translating biostatistics in the health sciences literature with clarity and irreverence. Students and practitioners alike applaud Biostatistics as a practical guide that exposes them to every statistical test they are likely to encounter, with careful conceptual explanations and a minimum of algebra. What's New? The previous edition of Bare Essentials presented hierarchical linear modeling, which first appeared in psychology journals and has only recently been described in the medical literature. The 3rd edition also introduced a chapter on testing for equivalence and non-inferiority as well as a chapter with information for getting started with the computer statistics program SPSS. A very positive review of the 3rd edition of the book by Dr. Naomi Vaisrub appeared in JAMA which praised the book but recommended covering topics in epidemiology, so in the 4th edition the authors took her up on it. They've also included an entirely new chapter, called "Measures of Impact," in which they discuss measures of incidence and prevalence, risk, morbidity and fatality rates, and the number needed to treat. They also delve into the Poisson distribution for doing regressions on count data. Likewise, the reader will find new sections on robust estimators of the mean, the problems of multiple hypothesis testing, bootstrapping and resampling, as well as an expanded section on nonparametric stats. Free of calculations and jargon, Bare Essentials speaks so plainly that you won't need a technical dictionary. The focus is on the concepts, not the math. The objective is to enable you to determine whether the research results are applicable to your own patients. Throughout, you'll find highlights of areas in which researchers misuse or misinterpret statistical tests. The authors have labeled these "C.R.A.P. Detectors" (Convoluted Reasoning and Anti-Intellectual Pomposity), and they help you identify faulty methodology and misuse of statistics.
ISBN: 9781607951780Publication Date: 2014-02-01
CiteSpace : a practical guide for mapping scientific literature by
CiteSpace is a freely available computer program written in Java for visualizing and analyzing literature of a scientific domain. A knowledge domain is broadly defined in order to capture the notion of a logically and cohesively organized body of knowledge. It may range from specific topics such as post-traumatic stress disorder to fields of study lacking clear-cut boundaries, such as research on terrorism or regenerative medicine. CiteSpace takes bibliographic information, especially citation information from the Web of Science, and generates interactive visualizations. Users can explore various patterns and trends uncovered from scientific publications, and develop a good understanding of scientific literature much more efficiently than they would from an unguided search through literature. The full text of many scientific publications can be accessed with a single click through the interactive visualization in CiteSpace. At the end of a session, CiteSpace can generate a summary report to summarize key information about the literature analyzed. This book is a practical guide not only on how to operate the tool but also on why the tool is designed and what implications of various patterns that require special attention. This book is written with a minimum amount of jargon. It uses everyday language to explain what people may learn from the writings of scholars of all kinds.
ISBN: 9781536102802Publication Date: 2016-01-01
Data Analysis with IBM SPSS Statistics : implementing data modeling, descriptive statistics and ANOVA by
Master data management & analysis techniques with IBM SPSS Statistics 24About This Book* Leverage the power of IBM SPSS Statistics to perform efficient statistical analysis of your data* Choose the right statistical technique to analyze different types of data and build efficient models from your data with ease* Overcome any hurdle that you might come across while learning the different SPSS Statistics concepts with clear instructions, tips and tricksWho This Book Is ForThis book is designed for analysts and researchers who need to work with data to discover meaningful patterns but do not have the time (or inclination) to become programmers. We assume a foundational understanding of statistics such as one would learn in a basic course or two on statistical techniques and methods. What You Will Learn* Install and set up SPSS to create a working environment for analytics* Techniques for exploring data visually and statistically, assessing data quality and addressing issues related to missing data* How to import different kinds of data and work with it* Organize data for analytical purposes (create new data elements, sampling, weighting, subsetting, and restructure your data)* Discover basic relationships among data elements (bivariate data patterns, differences in means, correlations)* Explore multivariate relationships* Leverage the offerings to draw accurate insights from your research, and benefit your decision-makingIn DetailSPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data.The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed.By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with ease.Style and approachProvides a practical orientation to understanding a set of data and examining the key relationships among the data elements. Shows useful visualizations to enhance understanding and interpretation. Outlines a roadmap that focuses the process so decision regarding how to proceed can be made easily.
ISBN: 9781787283817Publication Date: 2017-09-22
Educational Data Mining with R and Rattle by
Educational Data Mining (EDM) is one of the emerging fields in the pedagogy and andragogy paradigm. EDM concerns the techniques through which research data come from the educational domain. EDM is a promising discipline which has an imperative impact on predicting students' academic performance. It includes the transformation of existing, and the innovation of new approaches derived from multidisciplinary spheres of influence such as statistics, machine learning, psychometrics, scientific computing, etc. An archetype that is covered in this book is that of learning by example. The intention is that reader will easily be able to replicate the given examples and then adapt them to suit their own needs of teaching-learning. The content of the book is based on the research work undertaken by the authors on the theme "Mining of Educational Data for the Analysis and Prediction of Students' Academic Performance." The basic know-how presented in this book can be treated as a guide for educational data mining implementation using R and Rattle open source data mining tools. Technical topics discussed in the book include: * Emerging Research Directions in Educational Data Mining * Design Aspects and Developmental Framework of the System * Model Development - Building Classifiers * Educational Data Analysis: Clustering Approach
ISBN: 9788793379312Publication Date: 2016-04-05
Essential First Steps to Data Analysis : scenario-based examples using SPSS by
Carol S. Parke's Essential First Steps to Data Analysis: Scenario-Based Examples Using SPSS provides instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Such preparation may involve data management and manipulation tasks, data organization, structural changes to the data files, or conducting preliminary analysis. Twelve research-based scenarios are used to present the content. Each scenario tells the "story" of a researcher who thoroughly examined their data and the decisions they made along the way. The scenario begins with a description of the researcher's study and his/her data file(s), then describes the issues the researcher must address, explains why they are important, shows how SPSS was used to address the issues and prepare data, and shares the researcher's reflections and any additional decision-making. Finally, each scenario ends with the researcher's written summary of the procedures and outcomes from the initial data preparation or analysis.
ISBN: 9781412997515Publication Date: 2012-12-13
Exploiting Semantic Web Knowledge Graphs in Data Mining by
Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process.This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains.The book will be of interest to all those working in the field of data mining and KDD.
ISBN: 9781614999805Publication Date: 2019-06-28
Fuzzy System and Data Mining by
Fuzzy logic is widely used in machine control. The term 'fuzzy' refers to the fact that the logic involved can deal with concepts that cannot be expressed as either 'true' or 'false', but rather as 'partially true'. Fuzzy set theory is very suitable for modeling the uncertain duration in process simulation, as well as defining the fuzzy goals and fuzzy constraints of decision-making. It has many applications in industry, engineering and social sciences.This book presents the proceedings of the 2015 International Conference on Fuzzy Systems and Data Mining (FSDM2015), held in Shanghai, China, in December 2015. The application domain covers geography, biology, economics, medicine, the energy industry, social science, logistics, transport, industrial and production engineering, and computer science. The papers presented at the conference focus on topics such as system diagnosis, rule induction, process simulation/control, and decision-making. They include papers on solving practical problems with intelligent algorithms; statistical analysis; classification and clustering; and association rule learning. They also reflect the frontier in data mining research and address the challenges posed to data analytics research by the increasingly large datasets yielded by many application domains, together with new types of unstructured data.The book provides an overview of the ways in which fuzzy theory and data mining principles are applied in various fields, and will be of interest to all those who work in either the theory or practice of fuzzy systems and data mining.
ISBN: 9781614996187Publication Date: 2016-04-14
Handbook of Statistical Analysis and Data Mining Applications by
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas--from science and engineering, to medicine, academia and commerce.
ISBN: 9780124166325Publication Date: 2017-11-10
IBM SPSS Modeler Essentials : effective techniques for building powerful data mining and predictive analytics solutions by
Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS Modeler Key Features Get up-and-running with IBM SPSS Modeler without going into too much depth. Identify interesting relationships within your data and build effective data mining and predictive analytics solutions A quick, easy-to-follow guide to give you a fundamental understanding of SPSS Modeler, written by the best in the business Book Description IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler's easy to learn "visual programming" style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. Assessing a model's performance is as important as building it; this book will also show you how to do that. Finally, you will see how you can score new data and export your predictions. By the end of this book, you will have a firm understanding of the basics of data mining and how to effectively use Modeler to build predictive models. What you will learn Understand the basics of data mining and familiarize yourself with Modeler's visual programming interface Import data into Modeler and learn how to properly declare metadata Obtain summary statistics and audit the quality of your data Prepare data for modeling by selecting and sorting cases, identifying and removing duplicates, combining data files, and modifying and creating fields Assess simple relationships using various statistical and graphing techniques Get an overview of the different types of models available in Modeler Build a decision tree model and assess its results Score new data and export predictions Who this book is for This book is ideal for those who are new to SPSS Modeler and want to start using it as quickly as possible, without going into too much detail. An understanding of basic data mining concepts will be helpful, to get the best out of the book.
ISBN: 9781788291118Publication Date: 2017-12-26
Marketing Research with IBM® Spss Statistics : a practical guide by
Marketing researchers, companies and business schools need to be able to use statistical procedures correctly and accurately interpret the outputs, yet generally these people are scared off by the statistics behind the different analyses procedures, thus they often rely on external sources to come up with profound answers to the proposed research questions. In an accessible and step by step approach, the authors show readers which procedures to use in which particular situation and how to practically execute them using IBM®SPSS Statistics. IBM®is one of the largest statistical software providers world-wide and their IBM®SPSS Statistics software offers a very user-friendly environment. The program uses a simple drag-and-drop menu interface, which is also suitable for non-experienced programmers. It is widely employed in companies and many business schools also use this software package. This straightforward, pragmatic reference manual will help: professional marketers who use statistical procedures in in IBM®SPSS Statistics; undergraduate and postgraduate students where marketing research and research methodology are taught; all researchers analyzing survey-based data in a wide range of frontier domains like psychology, finance, accountancy, negotiation, communication, sociology, criminology, management, information systems, etc. IBM®'s next-generation business analytic solutions help organizations of all sizes make sense of information in the context of their business. You can uncover insights more quickly and easily from all types of data-even big data-and on multiple platforms and devices. And, with self-service and built-in expertise and intelligence, you have the freedom and confidence to make smarter decisions that better address your business imperatives.l will help: professional marketers who use statistical procedures in in IBM®SPSS Statistics; undergraduate and postgraduate students where marketing research and research methodology are taught; all researchers analyzing survey-based data in a wide range of frontier domains like psychology, finance, accountancy, negotiation, communication, sociology, criminology, management, information systems, etc. IBM®'s next-generation business analytic solutions help organizations of all sizes make sense of information in the context of their business. You can uncover insights more quickly and easily from all types of data-even big data-and on multiple platforms and devices. And, with self-service and built-in expertise and intelligence, you have the freedom and confidence to make smarter decisions that better address your business imperatives.
ISBN: 9781472477453Publication Date: 2016-07-28
Research Methods for the Behavioral Sciences by
Undergraduate students of psychology.
Call Number: BF76.5 .P65 2016ISBN: 9781506326573Publication Date: 2016-01-27
Using Software in Qualitative Research : a step-by-step guide by
Using Software in Qualitative Research is an essential introduction to the practice and principles of Computer Assisted Qualitative Data Analysis (CAQDAS). The book will help you to choose the most appropriate package for your needs and get the most out of the software once you are using it. This book considers a wide range of tasks and processes in the data management and analysis process, and shows how software can help you at each stage. In the new edition, the authors present three case studies with different forms of data (text, video and mixed data) and show how each step in the analysis process for each project could be supported by software. The new edition is accompanied by an extensive companion website with step-by-step instructions produced by the software developers themselves. Software programmes covered in second edition include the latest versions of: ATLAS.ti DEDOOSE HyperRESEARCH MAXQDA NVivo QDA Miner TRANSANA Ann Lewins and Christina Silver are leading experts in the field of CAQDAS and have trained thousands of students and researchers in using software. Reading this book is like having Ann and Christina at your shoulder as you analyse your data!
ISBN: 9781446249734Publication Date: 2014-06-30
