Features easy-to-follow insight and clear guidelines to performdata analysis using IBM SPSS® Performing Data Analysis Using IBM SPSS® uniquelyaddresses the presented statistical procedures with an exampleproblem, detailed analysis, and the related data sets. Data entryprocedures, variable naming, and step-by-step instructions for allanalyses are provided in addition to IBM SPSS point-and-clickmethods, including details on how to view and manipulateoutput. Designed as a user’s guide for students and otherinterested readers to perform statistical data analysis with IBMSPSS, this book addresses the needs, level of sophistication, andinterest in introductory statistical methodology on the part ofreaders in social and behavioral science, business, health-related,and education programs. Each chapter of Performing Data AnalysisUsing IBM SPSS covers a particular statistical procedure andoffers the following: an example problem or analysis goal, togetherwith a data set; IBM SPSS analysis with step-by-step analysis setupand accompanying screen shots; and IBM SPSS output with screenshots and narrative on how to read or interpret the results of theanalysis. The book provides in-depth chapter coverage of: IBM SPSS statistical output Descriptive statistics procedures Score distribution assumption evaluations Bivariate correlation Regressing (predicting) quantitative and categoricalvariables Survival analysis t Test ANOVA and ANCOVA Multivariate group differences Multidimensional scaling Cluster analysis Nonparametric procedures for frequency data Performing Data Analysis Using IBM SPSS is an excellenttext for upper-undergraduate and graduate-level students in courseson social, behavioral, and health sciences as well as secondaryeducation, research design, and statistics. Also an excellentreference, the book is ideal for professionals and researchers inthe social, behavioral, and health sciences; applied statisticians;and practitioners working in industry.
Master data management & analysis techniques with IBM SPSS Statistics 24 About 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 tricks Who This Book Is For This 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-making In Detail SPSS 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 approach Provides 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.
A Step by Step Guide to Data Analysis Using IBM SPSS
Author: Julie Pallant
Publisher: Allen & Unwin
Category: PASW (Computer file)
The internationally successful, user-friendly guide that takes students and researchers through the often daunting process of analysing research data with the widely used SPSS software package. Fully revised and updated for IBM SPSS Statistics version 23.
Public Health Research Methods, edited by Greg Guest and Emily Namey, provides a comprehensive foundation for planning, executing, and monitoring public health research of all types. The book goes beyond traditional epidemiologic research designs to cover state-of-the-art, technology-based approaches emerging in the new public health landscape. Written by experts in the field, each chapter includes a description of the research method covered, examples of its application in public health, clear instructions on how to execute the method, and a discussion of emerging issues and future directions. In addition, each chapter addresses the topic in the context of global health and health disparities. Such breadth provides readers with practical tools they can use in the field, as well as a current understanding of conceptual discussions. Illustrated with engaging case studies that enhance understanding of the concepts presented, Public Health Research Methods is a comprehensive, must-have reference ideal for researchers in all sectors—government, academia, and non-profit.
The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s “cut to the chase” IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.
Using a conceptual, non-mathematical approach, the updated Third Edition of Applied Multivariate Research: Design and Interpretation provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter. Authors Lawrence S. Meyers, Glenn Gamst, and A. J. Guarino integrate innovative multicultural topics in examples throughout the book, which include both conceptual and practical coverage of: statistical techniques of data screening; multiple regression; multilevel modeling; exploratory factor analysis; discriminant analysis; structural equation modeling; structural equation modeling invariance; survival analysis; multidimensional scaling; and cluster analysis.
Transforming data from operational data models to purpose-oriented data structures has been commonplace for the last decades. Data transformations are heavily used in all types of industries to provide information to various users at different levels. Depending on individual needs, the transformed data is stored in various different systems. Sending operational data to other systems for further processing is then required, and introduces much complexity to an existing information technology (IT) infrastructure. Although maintenance of additional hardware and software is one component, potential inconsistencies and individually managed refresh cycles are others. For decades, there was no simple and efficient way to perform data transformations on the source system of operational data. With IBM® DB2® Analytics Accelerator, DB2 for z/OS is now in a unique position to complete these transformations in an efficient and well-performing way. DB2 for z/OS completes these while connecting to the same platform as for operational transactions, helping you to minimize your efforts to manage existing IT infrastructure. Real-time analytics on incoming operational transactions is another demand. Creating a comprehensive scoring model to detect specific patterns inside your data can easily require multiple iterations and multiple hours to complete. By enabling a first set of analytical functionality in DB2 Analytics Accelerator, those dedicated mining algorithms can now be run on an accelerator to efficiently perform these modeling tasks. Given the speed of query processing on an accelerator, these modeling tasks can now be performed much quicker compared to traditional relational database management systems. This speed enables you to keep your scoring algorithms more up-to-date, and ultimately adapt more quickly to constantly changing customer behaviors. This IBM Redbooks® publication describes the new table type that is introduced with DB2 Analytics Accelerator V4.1 PTF5 that enables more efficient data transformations. These tables are called accelerator-only tables, and can exist on an accelerator only. The tables benefit from the accelerator performance characteristics, while maintaining access through existing DB2 for z/OS application programming interfaces (APIs). Additionally, we describe the newly introduced analytical capabilities with DB2 Analytics Accelerator V5.1, putting you in the position to efficiently perform data modeling for online analytical requirements in your DB2 for z/OS environment. This book is intended for technical decision-makers who want to get a broad understanding about the analytical capabilities and accelerator-only tables of DB2 Analytics Accelerator. In addition, you learn about how these capabilities can be used to accelerate in-database transformations and in-database analytics in various environments and scenarios, including the following scenarios: Multi-step processing and reporting in IBM DB2 Query Management FacilityTM, IBM Campaign, or Microstrategy environments In-database transformations using IBM InfoSphere® DataStage® Ad hoc data analysis for data scientists In-database analytics using IBM SPSS® Modeler
Using IBM® SPSS® Statistics: An Interactive Hands-On Approach, Third Edition gives readers an accessible and comprehensive guide to walking through SPSS®, providing them with step-by-step knowledge for effectively analyzing their data. From entering data to working with existing databases, and working with the help menu through performing factor analysis, Using IBM® SPSS® Statistics covers every aspect of SPSS® from introductory through intermediate statistics. The book is divided into parts that focus on mastering SPSS® basics, dealing with univariate statistics and graphing, inferential statistics, relational statistics, and more. Written using IBM® SPSS® version 25 and 24, and compatible with the earlier releases, this book is one of the most comprehensive SPSS® guides available.
Ideal as a companion to a statistics or research methods text or as a stand-alone guide, Using SPSS for Social Statistics and Research Methods shows readers how to use images and directions drawn from SPSS Version 18.0 and now uses the latest version of the GSS (General Social Survey) as a secondary data set. This supplementary text is designed as a manual for SPSS use for social statistics and research methods classes and is an excellent companion to any undergraduate statistics or research methods textbook. It will also serve as a useful reference for those learning to use the SPSS software for the first time. Features and Benefits: • Offers a fully updated graphics chapter that highlights new features available in SPSS 18.0, including information on alternative routes to creating graphics • Includes updated examples, screenshots and tables throughout • Expanded coverage of output interpretation • Refers to several kinds of computer files, including data files, output files and syntax files • Covers a wide range of data analysis topics to help students who are working independently on a research proposal, project or paper.
This supplementary text serves as a manual for SPSS use for social statistics and research methods classes. It is a useful guide for students working independently on a research proposal, project, or paper. Also, it is an excellent resource for instructors to use with some or all of the lab components of their course.