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SPSS Explained by Perry R. Hinton; Charlotte Brownlow; Isabella McMurray
SPSS Explained provides the student with all that they need to undertake statistical analysis using SPSS. It combines a step-by-step approach to each procedure with easy to follow screenshots at each stage of the process. A number of other helpful features are provided: regular advice boxes with tips specific to each test explanations divided into #65533;essential#65533; and #65533;advanced#65533; sections to suit readers at different levels frequently asked questions at the end of each chapter. The first edition of this popular book has been fully updated for IBM SPSS version 21 and also includes: chapters that explain bootstrapping and how this is used an introduction to binary logistic regression coverage of new features such as Chart Builder. Presented in full colour and with a fresh, reader-friendly layout, this fully updated new edition also comes with a companion website featuring an array of supplementary resources for students. The authors have many years of experience in teaching SPSS to students from a wide range of disciplines. Their understanding of SPSS users#65533; concerns, as well as a knowledge of the type of questions students ask, form the foundation of this book. Minimal prior knowledge is assumed, so the book is well designed for the novice user, but it will also be a useful reference source for those developing their own expertise in SPSS. It is suitable for all students who need to do statistical analysis using SPSS in various departments including Psychology, Social Science, Business Studies, Nursing, Education, Health and Sport Science, Communication and Media, Geography, and Biology.
ISBN: 9780415616010
Publication Date: 2014-04-30
Using Statistics in the Social and Health Sciences with Spss® and Excel® by Martin Lee Abbott
Provides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS#65533; and Excel#65533; applications This book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field. The book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material. Using Statistics in the Social and Health Sciences with SPSS#65533; and Excel#65533; includes: * Use of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings * Inclusion of a data lab section in each chapter that provides relevant, clear examples * Introduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs Emphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS#65533; and Excel#65533; for analyzing data. Martin Lee Abbott, PhD, is Professor of Sociology at Seattle Pacific University, where he has served as Executive Director of the Washington School Research Center, an independent research and data analysis center funded by the Bill & Melinda Gates Foundation. Dr. Abbott has held positions in both academia and industry, focusing his consulting and teaching in the areas of statistical procedures, program evaluation, applied sociology, and research methods. He is the author of Understanding Educational Statistics Using Microsoft Excel#65533; and SPSS#65533;, The Program Evaluation Prism: Using Statistical Methods to Discover Patterns, and Understanding and Applying Research Design, also from Wiley.
ISBN: 9781119121046
Publication Date: 2016-08-29
SPSS Statistics for Data Analysis and Visualization by Keith McCormick; Jesus Salcedo; Jon Peck; Jason Verlen (Foreword by); Andrew Wheeler
Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.
ISBN: 9781119003557
Publication Date: 2017-05-01
The Reference Guide to Data Sources by Julia Bauder
This concise sourcebook takes the guesswork out of locating the best sources of data, a process more important than ever as the data landscape grows incresingly cluttered. Much of the most frequently used data can be found free online, and this book shows readers how to look for it with the assistance of user-friendly tools. This thoroughly annotated guide will be a boon to library staff at public libraries, high school libraries, academic libraries, and other research institutions. It offers concentrated coverage of data sources for frequently researched subjects such as agriculture, the earth sciences, econiomics, energy, political science, and transportation; the basics of data reference along with an overview of the most useful sources; Statistical datasets, and how to understand and make use of them; and much more
ISBN: 9780838912270
Publication Date: 2014-06-01
The Art of Data Analysis by Kristin H. Jarman
A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: - Descriptive statistics - Analysis of variance - Probability and sample distributions - Confidence intervals - Hypothesis tests - Regression - Statistical correlation - Data collection - Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.
ISBN: 9781118411315
Publication Date: 2013-05-13
Information Quality by Ron S. Kenett; Galit Shmueli
Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.
ISBN: 9781118874448
Publication Date: 2016-12-19