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SPSS (The Statistical Package for the Social Sciences) is a computer program which enables data from surveys and experiments to be analyzed fully and flexibly. It has facilities for the extensive manipulation and transformation of data, and includes a wide range of procedures for both simple and highly complex statistical analysis. It also provides the opportu nity for the researcher to produce fully labelled tables and graphs which can be easily incorporated into a final project report. Over the 20 years since it was first devised, the versatile SPSS system has become an indispensable tool for many workers in social science research (including psychology, sociology, politics, human geography, business management, etc.) and in business and government. Many of the largest and most important surveys in the past two decades have been analyzed using one or other version of the system. SPSS is regularly used by government agencies, and by many major industrial corporations, market research companies and opinion poll organizations. For many years SPSS could be run only on large (mainframe) computers of the kind found in the specialist computer installations within universities and large corporations. Advances in the speed, power and memory of microcomputers, however, have recently made it possible to produce a powerful version of SPSS for use on the desk-top machines of the IBM PC (personal computer) family.
The PASW Statistics 19 Guide to Data Analysis is a friendly introduction to both data analysis and PASW Statistics 19 (formerly SPSS Statistics), the world's leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. With this book, you'll learn how to describe data, test hypotheses, and examine relationships using PASW. Author Marija Noru is incorporates a wealth of real data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners, throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun! A data CD-ROM is included with this book.
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.
Boslaugh (pediatrics, Washington U. School of Medicine) describes the use of SPSS, the statistical analysis package, and its syntax for data management. Assuming no familiarity with the software, he describes basic computer programming with SPSS, reading and writing data files, file manipulation and management, variables and variable management, an
This text is designed to teach beginners how to use SPSS for Windows. The author explains the basics of SPSS, including: the input of data; data manipulation; descriptive analyses; and inferential techniques. T-tests, analysis of variance, and factor analysis are also covered.
This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of R and RStudio code, and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.
The 3rd edition of A Student Guide to SPSS provides easy to follow step-by-step instructions on how to compute introductory and advanced statistics using one of the most popular statistical software programs in psychology, business, education, and other social sciences. Written in a non-intimidating, easy to read language, this guide is suitable for individuals with little to no experience using statistical software. As such, it would be of practical use to anyone who needs a simple and straightforward introduction to the most commonly used features of SPSS. This guide to SPSS was originally developed to complement the lecture component of introductory undergraduate courses in statistics. The 2nd and 3rd editions were expanded to increase the guide's suitability for more advanced undergraduate statistics courses. While most statistics textbooks teach students how to hand calculate statistics, this guide gives students the opportunity to learn how to analyze large datasets not conducive to hand calculations, providing them with the practical skills necessary for graduate school and/or a career in research. Features Learning objectives at the beginning of each chapter help students keep on track and instructors apprised of the functions that students have learned so they can create SPSS assignments for students. Concrete examples with screenshots of SPSS are used throughout to make it easier for students to learn how to compute and interpret statistics. Examples of reporting statistics in the style of the American Psychological Association (APA)- using the 7th edition of their manual- are included. New to the Third Edition Throughout the guide, elaborations on the meaning and interpretation of various statistics and demonstrations of more advanced statistical analyses have been added. The chapter on multiple regression has been expanded to include a new example that describes how to include a nominal predictor variable with more than two categories in a multiple regression analysis as well as how to interpret the results. A brief discussion of the tolerance statistic has been added to the advanced regression chapter. The chapter on one-way ANOVA has been expanded to include one-way within-groups ANOVA (in addition to one-way between-groups ANOVA). Content The 3rd edition of A Student Guide to SPSS contains 9 chapters on getting started with SPSS, descriptive statistics, correlation, simple regression, multiple regression, advanced regression (hierarchal regression, stepwise regression), the sign test, t-tests (single sample, paired samples, independent samples), and one-way ANOVA (one-way between, one-way within).
'The PASW and SPSS Survival Manual' throws a lifeline to students and researchers grappling with this data analysis software. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, the author discusses basic and advanced statistical techniques.
What statistical test should I use for this kind of data? How do I set up the data? What parameters should I specify when ordering the test? How do I interpret the results? Herschel Knapp′s friendly and approachable guide to real-world statistics answers these questions. Intermediate Statistics Using SPSS is not about abstract statistical theory or the derivation or memorization of statistical formulas–it is about applied statistics. With jargon-free language and clear processing instructions, this text covers the most common statistical functions–from basic to more advanced. Practical exercises at the conclusion of each chapter offer students an opportunity to process viable data sets, write cohesive abstracts in APA style, and build a thorough comprehension of the statistical process. Students will learn by doing with this truly practical approach to statistics.
Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.