SPSS 16.0 Guide to Data Analysis


Book Description

The SPSS 16.0 Guide to Data Analysis is a friendly introduction to both data analysis and SPSS, 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 the SPSS 16.0 Guide to Data Analysis, you get a jump-start on describing data, testing hypotheses, and examining relationships using SPSS. Author Marija Noru is incorporates a wealth of 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. These data files are supplied with the book and are used 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! Data CD-ROM included.




SPSS 12.0 Brief Guide


Book Description

"A student version of the world's leading desktop statistical software"--Box.




How to Use SPSS®


Book Description

How to Use SPSS® is designed with the novice computer user in mind and for people who have no previous experience of using SPSS. Each chapter is divided into short sections that describe the statistic being used, important underlying assumptions, and how to interpret the results and express them in a research report. The book begins with the basics, such as starting SPSS, defining variables, and entering and saving data. It covers all major statistical techniques typically taught in beginning statistics classes, such as descriptive statistics, graphing data, prediction and association, parametric inferential statistics, nonparametric inferential statistics and statistics for test construction. More than 250 screenshots (including sample output) throughout the book show students exactly what to expect as they follow along using SPSS. The book includes a glossary of statistical terms and practice exercises. A complete set of online resources including video tutorials and output files for students, and PowerPoint slides and test bank questions for instructors, make How to Use SPSS® the definitive, field-tested resource for learning SPSS. New to this edition: Fully updated to SPSS 24 and IBM SPSS Statistics Cloud New chapter on ANOVA New material on inter-rater reliability New material on syntax Additional coverage of data entry and management




Quantitative Data Analysis with Minitab


Book Description

Quantitative data analysis is now a compulsory component of most degree courses in the social sciences and students are increasingly reliant on computers for the analysis of data. Quantitative Data Analysis with Minitab explains statistical tests for Minitab users using the same formulae free, non technical approach, as the very successful SPPS version. Students will learn a wide range of quantitative data analysis techniques and become familiar with how these techniques can be implemented through the latest version of Minitab. Techniques covered include univariate analysis (with frequency table, dispersion and histograms), bivariate (with contingency tables correlation, analysis of varience and non-parametric tests) and multivariate analysis (with multiple regression, path analysis, covarience and factor analysis). In addition the book covers issues such as sampling, statistical significance, conceptualisation and measurement and the selection of appropriate tests. Each chapter concludes with a set of exercises. Social science students will welcome this integrated, non mathematical introduction to quantitative data anlysis and the minitab package.




SPSS Survival Manual


Book Description

The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling manual, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic through to advanced statistical techniques. She outlines each technique clearly, providing step by step procedures for performing your analysis, a detailed guide to interpreting data output and examples of how to present your results in a report. For both beginners and experienced users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is an essential text. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. This seventh edition is fully revised and updated to accommodate changes to IBM SPSS Statistics procedures, screens and output. 'An excellent introduction to using SPSS for data analysis. It provides a self-contained resource itself, with more than simply (detailed and clear) step-by-step descriptions of statistical procedures in SPSS. There is also a wealth of tips and advice, and for each statistical technique a brief, but consistently reliable, explanation is provided.' - Associate Professor George Dunbar, University of Warwick 'This book is recommended as ESSENTIAL to all students completing research projects - minor and major.' - Dr John Roodenburg, Monash University A website with support materials for students and lecturers is available at www.spss.allenandunwin.com




SPSS 12.0 Statistical Procedures Companion


Book Description

SPSS(R) 12.0 Statistical Procedures Companion Whether you are just getting started with statistics or moving into more advanced analyses, this book will help you get the most out of your time and data and exploit the power of the SPSS system. Here's what you'll find: An introduction to the SPSS system, with an emphasis on how to prepare data for analysis Practical discussions of the statistical background for each of the statistical procedures Detailed examples from diverse areas, including psychology, sociology, education, archaeology, medicine, library science, nursing, and journalism Numerous tips and warnings to help you work efficiently and avoid common pitfalls A CD containing many of the data sets used in the book Coverage of statistics starts with the basics and extends to the most powerful modeling procedures, showing you how to: Analyze data using simple statistical procedures (descriptive statistics, comparisons of means, correlation, bivariate regression, and nonparametric tests) Employ more complex statistical procedures (multiple regression, factor analysis, discriminant analysis, logistic regression, cluster analysis, and reliability) Build models with the general linear model (univariate, multivariate, and repeated measures) Analyze correlated observations with linear mixed models




IBM SPSS Statistics Excellent Guide


Book Description

IBM SPSS Statistics Excellent Guide is an excellent illustrative point-by-point easy to use guide that guarantees everyone the revolutionary skills of data analysis with SPSS Statistics. What if you can personally analyze different sorts of research data accurately without a hand-held calculator? Yes, you can. Each user of the book can with all accuracy, perform data analysis expertly and lucidly interpret the output, even if it is his first day of utilizing SPSS. IBM SPSS Statistics is renowned as a most powerful and widely used software for data analysis in the social and behavioral sciences, particularly, and in other several different fields of endeavor. Currently, practical analytic skills with statistical software as demonstrated in this book are necessarily required to be a researcher or scientist. Peter James Kpolovie has provided a superb guide that thoroughly presents SPSS dialog boxes selection method and SPSS syntax method for myriads of introductory and advanced statistical techniques, including: Descriptive statistics Comparison of means with t Test techniques and Analysis of Variance models General Linear Models Univariate, Repeated measures and Mixed analysis Analysis of Covariance To accurately analyze large complex dataset collected for a given research, has consistently remained a major challenge to the investigator even before the actual problem that he has set out to investigate. Kpolovie has superbly eliminated such challenge as every user can with most exceptional ease, follow the complete procedural steps, famously illustrated in the book, to personally analyze various sorts of data impeccably. Buy a copy now and acquire mastery of the new skills.




IBM SPSS Statistics 19 Guide to Data Analysis


Book Description

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.




Performing Data Analysis Using IBM SPSS


Book Description

Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS® Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output. Designed as a user’s guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis. 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 categorical variables 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 excellent text for upper-undergraduate and graduate-level students in courses on social, behavioral, and health sciences as well as secondary education, research design, and statistics. Also an excellent reference, the book is ideal for professionals and researchers in the social, behavioral, and health sciences; applied statisticians; and practitioners working in industry.




SPSS 16.0 Brief Guide


Book Description

TheSPSS 16.0 Brief Guide provides a set of tutorials to acquaint you with the components of the SPSS system. Topics include reading data, using the Data Editor, examining summary statistics for individual variables, working with output, creating and editing charts, working with syntax, modifying data values, sorting and selecting data, and performing additional statistical procedures.