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| discriminant analysis interpretation spss: Applied Multivariate Research Lawrence S. Meyers, Glenn Gamst, A.J. Guarino, 2006 Multivariate designs were once the province of the very few exalted researchers who understood the underlying advanced mathematics. Today, through the sophistication of statistical software packages such as SPSS, virtually all graduate students across the social and behavioural sciences are exposed to the complex multivariate statistical techniques without having to learn the mathematical computations needed to acquire the data output. These students - in psychology, education, political science, etc. - will never be statisticians and appropriately so, their preparation and coursework reflects less of an emphasis on the mathematical complexities of multivariate statistics and more on the analysis and the interpretation of the methods themselves and the actual data output. This book provides full coverage of the wide range of multivariate topics in a conceptual, rather than mathematical, approach. The author gears toward the needs, level of sophistication, and interest in multivariate methodology of students in applied areas that need to focus on design and interpretation rather than the intricacies of specific computations. The book includes: - Coverage of the most widely used multivariate designs: multiple regression, exploratory factor analysis, MANOVA, and structural equation modeling. - Integrated SPSS examples for hands-on learning from one large study (for consistency of application throughout the text). - Examples of written results to enable students to learn how the results of these procedures are communicated. - Practical application of the techniques using contemporary studies that will resonate with students. |
| discriminant analysis interpretation spss: SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics Daniel J. Denis, 2018-09-25 Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics offers a variety of popular statistical analyses and data management tasks using SPSS that readers can immediately apply as needed for their own research, and emphasizes many helpful computational tools used in the discovery of empirical patterns. The book begins with a review of essential statistical principles before introducing readers to SPSS. The book then goes on to offer chapters on: Exploratory Data Analysis, Basic Statistics, and Visual Displays; Data Management in SPSS; Inferential Tests on Correlations, Counts, and Means; Power Analysis and Estimating Sample Size; Analysis of Variance – Fixed and Random Effects; Repeated Measures ANOVA; Simple and Multiple Linear Regression; Logistic Regression; Multivariate Analysis of Variance (MANOVA) and Discriminant Analysis; Principal Components Analysis; Exploratory Factor Analysis; and Non-Parametric Tests. This helpful resource allows readers to: Understand data analysis in practice rather than delving too deeply into abstract mathematical concepts Make use of computational tools used by data analysis professionals. Focus on real-world application to apply concepts from the book to actual research Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks. |
| discriminant analysis interpretation spss: Analyzing Quantitative Data Debra Wetcher-Hendricks, 2014-08-21 A user-friendly, hands-on guide to recognizing and conducting proper research techniques in data collection Offering a unique approach to numerical research methods, Analyzing Quantitative Data: An Introduction for Social Researchers presents readers with the necessary statistical applications for carrying out the key phases of conducting and evaluating a research project. The book guides readers through the steps of data analysis, from organizing raw data to utilizing descriptive statistics and tests of significance, drawing valid conclusions, and writing research reports. The author successfully provides a presentation that is accessible and hands-on rather than heavily theoretical, outlining the key quantitative processes and the use of software to successfully draw valid conclusions from gathered data. In its discussion of methods for organizing data, the book includes suggestions for coding and entry into spreadsheets or databases while also introducing commonly used descriptive statistics and clarifying their roles in data analysis. Next, inferential statistics is explored in-depth with explanations of and instructions for performing chi-square tests, t-tests, analyses of variance, correlation and regression analyses, and a number of advanced statistical procedures. Each chapter contains explanations of when to use the tests described, relevant formulas, and sample computations. The book concludes with guidance on extracting meaningful conclusions from statistical tests and writing research reports that describe procedures and analyses. Throughout the book, Statistical Resources for SPSS® sections provide fundamental instruction for using SPSS® to obtain the results presented. Where necessary, the author provides basic theoretical explanations for distributions and background information regarding formulas. Each chapter concludes with practice problems, and a related website features derivations of the book's formulas along with additional resources for performing the discussed processes. Analyzing Quantitative Data is an excellent book for social sciences courses on data analysis and research methods at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians and practitioners working in the fields of education, medicine, business and public service who analyze, interpret, and evaluate data in their daily work. |
| discriminant analysis interpretation spss: Statistical Methods of Discrimination and Classification Sung C. Choi, Ervin Y. Rodin, 2014-05-17 Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a collection of papers that tackles the multivariate problems of discriminating and classifying subjects into exclusive population. The book presents 13 papers that cover that advancement in the statistical procedure of discriminating and classifying. The studies in the text primarily focus on various methods of discriminating and classifying variables, such as multiple discriminant analysis in the presence of mixed continuous and categorical data; choice of the smoothing parameter and efficiency of k-nearest neighbor classification; and assessing the performance of an allocation rule. The book will be of great use to researchers and practitioners of wide array of scientific disciplines, including engineering, psychology, biology, and physics. |
| discriminant analysis interpretation spss: Discovering Statistics Using IBM SPSS Statistics Andy Field, 2024-02-22 With its unique combination of humour and step-by-step instruction, this award-winning book is the statistics lifesaver for everyone. From initial theory through to regression, factor analysis and multilevel modelling, Andy Field animates statistics and SPSS software with his famously bizarre examples and activities. Features: • Flexible coverage to support students across disciplines and degree programmes • Can support classroom or lab learning and assessment • Analysis of real data with opportunities to practice statistical skills • Highlights common misconceptions and errors • A revamped online resource that uses video, case studies, datasets, testbanks and more to help students negotiate project work, master data management techniques, and apply key writing and employability skills • Covers the range of versions of IBM SPSS Statistics©. All the online resources above (video, case studies, datasets, testbanks) can be easily integrated into your institution′s virtual learning environment or learning management system. This allows you to customize and curate content for use in module preparation, delivery and assessment. |
| discriminant analysis interpretation spss: Data Analysis in Management with SPSS Software J.P. Verma, 2012-12-13 This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS. It strengthens the intuitive understanding of the material, thereby increasing the ability to successfully analyze data in the future. The book provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of research problems. This book focuses on providing readers with the knowledge and skills needed to carry out research in management, humanities, social and behavioural sciences by using SPSS. |
| discriminant analysis interpretation spss: Discriminant Analysis William R. Klecka, 1980-08 Background. Deriving the canonical discriminant functions. Interpreting the canonical discriminant functions. Classification procedures. Stepwise inclusion of variables. Concluding remarks. |
| discriminant analysis interpretation spss: Advanced and Multivariate Statistical Methods Craig A. Mertler, Rachel A. Vannatta, Kristina N. LaVenia, 2021-11-29 Advanced and Multivariate Statistical Methods, Seventh Edition provides conceptual and practical information regarding multivariate statistical techniques to students who do not necessarily need technical and/or mathematical expertise in these methods. This text has three main purposes. The first purpose is to facilitate conceptual understanding of multivariate statistical methods by limiting the technical nature of the discussion of those concepts and focusing on their practical applications. The second purpose is to provide students with the skills necessary to interpret research articles that have employed multivariate statistical techniques. Finally, the third purpose of AMSM is to prepare graduate students to apply multivariate statistical methods to the analysis of their own quantitative data or that of their institutions. New to the Seventh Edition All references to SPSS have been updated to Version 27.0 of the software. A brief discussion of practical significance has been added to Chapter 1. New data sets have now been incorporated into the book and are used extensively in the SPSS examples. All the SPSS data sets utilized in this edition are available for download via the companion website. Additional resources on this site include several video tutorials/walk-throughs of the SPSS procedures. These how-to videos run approximately 5–10 minutes in length. Advanced and Multivariate Statistical Methods was written for use by students taking a multivariate statistics course as part of a graduate degree program, for example in psychology, education, sociology, criminal justice, social work, mass communication, and nursing. |
| discriminant analysis interpretation spss: SPSS for Intermediate Statistics Nancy L. Leech, Karen Caplovitz Barrett, George Arthur Morgan, 2005 Intended as a supplement for intermediate statistics courses taught in departments of psychology, education, business, and other health, behavioral, and social sciences. |
| discriminant analysis interpretation spss: SPSS 12 Made Simple Paul Kinnear, Colin Gray, 2006-02-06 SPSS 12 Made Simple provides a step-by-step coverage of every aspect of data analysis with SPSS from data entry to interpretation of the output. As well as advice on data entry and checking, there is guidance on the best ways of describing a data set and the choice of an appropriate statistical technique. Finally, the output is fully explained, with reference to fully annotated SPSS output. Extensive illustrations show exactly what is on the screen at every stage of the process, helping the reader to avoid common pitfalls and check their progress along the way. Most chapters end with practical exercises to illustrate the main points raised and allow the reader to test their understanding; but there is a final general revision section with further exercises on a range of topics. In view of the recommendations of the American Psychological Association, the book now contains advice on strength of effect, power and sample size. There is also guidance on how to report the results of statistical tests in journal articles. This new edition is written with the same clarity that has made the book such a success in the past. The initial chapters provide an introduction to the basics of SPSS, such as data entry, followed by more advanced techniques, such as sorting, case selection, aggregation and file merging. In these early chapters, the emphasis is upon checking the accuracy of data entry and exploring the data thoroughly before making any formal statistical tests. There is also extensive coverage of the powerful new graphics capabilities of SPSS 12. Each of the later chapters is devoted to a particular statistical technique. SPSS 12 Made Simple: *Covers a wide range of statistical tests including t-tests, ANOVA, correlation, regression, multi-way frequency analysis, discriminant analysis, logistic regression and factor analysis. *Shows you how to get as much out of your data as possible. *Gives advice (with appropriate cautions and caveats) on choosing a statistical test. *Makes extensive use of annotated screen snapshots of SPSS output, windows and dialog boxes. *Includes both chapter-specific and general exercises. *Has a comprehensive index. |
| discriminant analysis interpretation spss: SPSS for Windows Made Simple Paul R. Kinnear, Colin D. Gray, 1999 This new edition incorporates recent developments in SPSS (and in Windows) by drawing upon screen images, dialog boxes and output from SPSS 8 in the Windows 95 environment. A feature of SPSS 8 is the new, powerful Viewer output manager, which enables the user to produce better tables, charts and graphs by affording greater editorial control over both content and appearance than was possible in previous versions. The first six chapters (on data handling and exploration, graph plotting and two-sample statistical tests) and the associated exercises provide an introduction to the basics of working with SPSS, while the remaining chapters cover more advanced topics such as various ANOVA designs, correlation and regression, loglinear analysis, discriminant anlysis and factor analysis. In response to the comments of readers worldwide, the authors have expanded sections on the inputting and exploration of data, graphical procedures and advice on choosing appropriate statistical tests. The remaining chapters have also been revised. Where appropriate, chapters include images of dialog boxes, output listings and exercises for student courses. |
| discriminant analysis interpretation spss: The Critical Mass in Collective Action Gerald Marwell, Pamela Oliver, 1993-03-26 The problem of collective action is that each group member wants other members to make necessary sacrifices while he or she 'free rides', reaping the benefits of collective action without doing the work. Therefore, no one does the work and the common interest is not realized. This book analyses the social pressure whereby groups solve the problem of collective action. |
| discriminant analysis interpretation spss: Analysing Quantitative Data Raymond A Kent, 2015-03-16 This innovative book provides a fresh take on quantitative data analysis within the social sciences. It presents variable-based and case-based approaches side-by-side encouraging you to learn a range of approaches and to understand which is the most appropriate for your research. Using two multidisciplinary non-experimental datasets throughout, the book demonstrates that data analysis is really an active dialogue between ideas and evidence. Each dataset is returned to throughout the chapters enabling you to see the role of the researcher in action; it also showcases the difference between each approach and the significance of researchers’ decisions that must be made as you move through your analysis. The book is divided into four clear sections: Data and their presentation Variable-based analyses Case-based analyses Comparing and combining approaches Clear, original and written for students this book should be compulsory reading for anyone looking to conduct non-experimental quantitative data analysis. |
| discriminant analysis interpretation spss: Handbook of Univariate and Multivariate Data Analysis with IBM SPSS Robert Ho, 2013-10-25 Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. This second edition now covers more topics |
| discriminant analysis interpretation spss: SPSS for Macintosh Made Simple Colin D. Gray, Paul R. Kinnear, 1998 SPSS for Macintosh Made Simple is an introductory guide for the Macintosh user. This book has all the features of the successful & highly acclaimed book by the same authors, SPSS for Windows Made Simple, 2nd Edition (Psychology Press, 1997). There is an abundance of worked examples, which include annotated SPSS output listings & actual screen images, icons & dialog boxes. These are accompanied by comments clarifying the points that have arisen most frequently from students' queries during practical classes run by the authors. The range of problems & techniques covered is much wider than in comparable introductory texts, & this book will prove invaluable to the experienced researcher & the undergraduate alike. The text includes a complete course of practical exercises covering all the main topics considered in the text. This book: introduces the reader to the Macintosh environment for SPSS; shows the reader how to explore & depict a set of data; gives advice on choosing a statistical test; includes important cautions & caveats about the use of statistics; illustrates techniques with fully annotated SPSS menus, dialog boxes & output; contains an abundance of worked examples & exercises for the reader; has a comprehensive table of contents & index. |
| discriminant analysis interpretation spss: Applied Multivariate Statistical Concepts Debbie L. Hahs-Vaughn, 2024-10-29 This second edition of Applied Multivariate Statistical Concepts covers the classic and cutting-edge multivariate techniques used in today’s research. Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio helps readers master key concepts so they can implement and interpret results generated by today’s sophisticated software. Additional features include examples using real data from the social sciences; templates for writing research questions and results that provide manuscript-ready models; step-by-step instructions on using R and SPSS statistical software with screenshots and annotated output; clear coverage of assumptions, including how to test them and the effects of their violation; and conceptual, computational, and interpretative example problems that mirror the real-world problems students encounter in their studies and careers. This edition features expanded coverage of topics, such as propensity score analysis, path analysis and confirmatory factor analysis, and centering, moderation effects, and power as related to multilevel modelling. New topics are introduced, such as addressing missing data and latent class analysis, while each chapter features an introduction to using R statistical software. This textbook is ideal for courses on multivariate statistics/analysis/design, advanced statistics, and quantitative techniques, as well as for graduate students broadly in social sciences, education, and behavioral sciences. It also appeals to researchers with no training in multivariate methods. |
| discriminant analysis interpretation spss: Approaching Multivariate Analysis, 2nd Edition Pat Dugard, John Todman, Harry Staines, 2022-06-30 This fully updated new edition not only provides an introduction to a range of advanced statistical techniques that are used in psychology, but has been expanded to include new chapters describing methods and examples of particular interest to medical researchers. It takes a very practical approach, aimed at enabling readers to begin using the methods to tackle their own problems. This book provides a non-mathematical introduction to multivariate methods, with an emphasis on helping the reader gain an intuitive understanding of what each method is for, what it does and how it does it. The first chapter briefly reviews the main concepts of univariate and bivariate methods and provides an overview of the multivariate methods that will be discussed, bringing out the relationships among them, and summarising how to recognise what types of problem each of them may be appropriate for tackling. In the remaining chapters, introductions to the methods and important conceptual points are followed by the presentation of typical applications from psychology and medicine, using examples with fabricated data. Instructions on how to do the analyses and how to make sense of the results are fully illustrated with dialogue boxes and output tables from SPSS, as well as details of how to interpret and report the output, and extracts of SPSS syntax and code from relevant SAS procedures. This book gets students started, and prepares them to approach more comprehensive treatments with confidence. This makes it an ideal text for psychology students, medical students and students or academics in any discipline that uses multivariate methods. |
| discriminant analysis interpretation spss: Advancing Quantitative Methods in Second Language Research Luke Plonsky, 2015-07-03 Advancing Quantitative Methods in Second Language Research is the first hands-on guide to conducting advanced research methods in the fields of applied linguistics and second language studies. While a number of texts discuss basic quantitative research methodology, none focus exclusively on providing coverage of alternative advanced statistical procedures in second language studies from a practical approach. The text is bookended by discussions of these advanced procedures in the larger context of second language studies, debating their strengths, weaknesses, and potential for further research; the remaining chapters are how-to sections, each chapter following the same organization, on a wide variety of advanced research methods. By offering much-needed coverage on advanced statistical concepts and procedures, with an eye toward real-world implementation, Advancing Quantitative Methods in Second Language Research enhances the methodological repertoire of graduate students and researchers in applied linguistics and second language studies. For additional content, visit: http://oak.ucc.nau.edu/ldp3/AQMSLR.html |
| discriminant analysis interpretation spss: Applied Univariate, Bivariate, and Multivariate Statistics Daniel J. Denis, 2015-12-14 A clear and efficient balance between theory and application of statistical modeling techniques in the social and behavioral sciences Written as a general and accessible introduction, Applied Univariate, Bivariate, and Multivariate Statistics provides an overview of statistical modeling techniques used in fields in the social and behavioral sciences. Blending statistical theory and methodology, the book surveys both the technical and theoretical aspects of good data analysis. Featuring applied resources at various levels, the book includes statistical techniques such as t-tests and correlation as well as more advanced procedures such as MANOVA, factor analysis, and structural equation modeling. To promote a more in-depth interpretation of statistical techniques across the sciences, the book surveys some of the technical arguments underlying formulas and equations. Applied Univariate, Bivariate, and Multivariate Statistics also features Demonstrations of statistical techniques using software packages such as R and SPSS® Examples of hypothetical and real data with subsequent statistical analyses Historical and philosophical insights into many of the techniques used in modern social science A companion website that includes further instructional details, additional data sets, solutions to selected exercises, and multiple programming options An ideal textbook for courses in statistics and methodology at the upper- undergraduate and graduate-levels in psychology, political science, biology, sociology, education, economics, communications, law, and survey research, Applied Univariate, Bivariate, and Multivariate Statistics is also a useful reference for practitioners and researchers in their field of application. DANIEL J. DENIS, PhD, is Associate Professor of Quantitative Psychology at the University of Montana where he teaches courses in univariate and multivariate statistics. He has published a number of articles in peer-reviewed journals and has served as consultant to researchers and practitioners in a variety of fields. |
| discriminant analysis interpretation spss: Research Methods in Public Administration and Nonprofit Management David E. McNabb, 2017-09-11 Now in a thoroughly revised and refreshed fourth edition, Research Methods in Public Administration and Nonprofit Management is beloved by students and professors alike for its exceptional clarity and accessibility and plentiful illustrations. This new edition integrates quantitative, qualitative, and mixed-methods approaches, as well as specific up-to-date instruction in the use of statistical software programs such as Excel and SPSS. Changes to this edition include: A new section, featuring two new chapters, to explore mixed-methods approaches to research, including fundamentals, research design, data collection, and analyzing and interpreting findings A new, dedicated chapter on Big Data research Updated exhibits and examples throughout the book A new companion website to accompany the book containing PowerPoint slides for each chapter New exhibits, tables, figures, and exercises, as well as key terms and discussion questions at the end of each chapter Research Methods in Public Administration and Nonprofit Management, 4e is an ideal textbook for use in all research methods courses in undergraduate and graduate public administration, public affairs, and nonprofit management courses. |
| discriminant analysis interpretation spss: Multivariate Methods and Forecasting with IBM® SPSS® Statistics Abdulkader Aljandali, 2017-07-06 This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naïve techniques. This part also covers hot topics such as Factor Analysis, Discriminant Analysis and Multidimensional Scaling (MDS). |
| discriminant analysis interpretation spss: Multivariate Analysis Klaus Backhaus, Bernd Erichson, Sonja Gensler, Rolf Weiber, Thomas Weiber, 2023-06-28 Data can be extremely valuable if we are able to extract information from them. This is why multivariate data analysis is essential for business and science. This book offers an easy-to-understand introduction to the most relevant methods of multivariate data analysis. It is strictly application-oriented, requires little knowledge of mathematics and statistics, demonstrates the procedures with numerical examples and illustrates each method via a case study solved with IBM’s statistical software package SPSS. Extensions of the methods and links to other procedures are discussed and recommendations for application are given. An introductory chapter presents the basic ideas of the multivariate methods covered in the book and refreshes statistical basics which are relevant to all methods. For the 2nd edition, all chapters were checked and calculated using the current version of IBM SPSS. Contents Introduction to empirical data analysis Regression analysis Analysis of variance Discriminant analysis Logistic regression Contingency analysis Factor analysis Cluster analysis Conjoint analysis The original German version is now available in its 17th edition. In 2015, this book was honored by the Federal Association of German Market and Social Researchers as “the textbook that has shaped market research and practice in German-speaking countries”. A Chinese version is available in its 3rd edition. On the website www.multivariate-methods.info, the authors further analyze the data with Excel and R and provide additional material to facilitate the understanding of the different multivariate methods. In addition, interactive flashcards are available to the reader for reviewing selected focal points. Download the Springer Nature Flashcards App and use exclusive content to test your knowledge. |
| discriminant analysis interpretation spss: Illustrating Statistical Procedures: Finding Meaning in Quantitative Data Ray W. Cooksey, 2020-05-14 This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis. |
| discriminant analysis interpretation spss: Quantitative Social Research Methods Kultar Singh, 2007-03-06 Quantitative Social Research Methods explores the entire spectrum of quantitative social research methods and their application, with special reference to the development sector. It provides detailed coverage of all statistical research and analysis method with an emphasis on multivariate analysis techniques, such as regression discriminant analysis, logistic regression, factor, factor, cluster, correspondence and conjoint analysis. The book is thematically arranged in two sections: the first section introduces development research techniques, explores the genesis and scope of social research, research processes and then goes on to explain univariate, bivariate and multivariate data analysis with the help of software packages such as SPSS and STATA. The second focuses on the application of social and development research methods in the development sector. It explores research method application and the issues relevant to aspects of development such as population, health and nutrition, poverty and rural development, education, water and sanitation, and environment and natural resource management. |
| discriminant analysis interpretation spss: Research Methodology: Concepts and Cases Deepak Chawla & Neena Sodhi, 2011 RESEARCH METHODOLOGY CONCEPT AND CASES provides a comprehensive and stepwise understanding of the research process with a balanced blend of theory, techniques and Indian illustrations from a wide cross-section of business areas. This book makes no presumptions and can be used with confidence and conviction by both students and experienced managers who need to make business sense of the data and information that is culled out through research groups. The conceptual base has been provided in comprehensive, yet simplistic detail, addressing even the minutest explanations required by the reader. The language maintains a careful balance between technical know-how and business jargon. Every chapter is profusely illustrated with business problems related to all domains—marketing, finance, human resource and operations. Thus, no matter what the interest area may be, the universal and adaptable nature of the research process is concisely demonstrated. |
| discriminant analysis interpretation spss: Fish and Diadromy in Europe (ecology, management, conservation) Sylvie Dufour, Etienne Prevost, Eric Rochard, Patrick Williot, 2008-08-24 Most of the diadromous fish of the world have decreased in distribution and abundance since the beginning of the twentieth century. They are now threatened, and important conservation issues arise. The causes of these trends vary among species and basins but regional human impact (damming, pollution, fisheries) and global change (climate) are suspected to be responsible for these difficulties. This book contains selected papers from an international symposium organised by the Diadfish network held in Bordeaux (France) in 2005. Readers will find up-to-date information on the ecology, ecotoxicology and physiology of several diadromous species (Atlantic salmon, shads, lampreys, eels) and this whole group in Europe. Main impacts are also documented and analysed in case studies, and solutions or remediation actions are presented. |
| discriminant analysis interpretation spss: Research Methods and Design in Sport Management Damon P. S. Andrew, Paul Mark Pedersen, Chad D. McEvoy, 2011 This text explains research design, implementation, analysis and assessment criteria with a focus on specific procedures unique to sport managament. |
| discriminant analysis interpretation spss: Business Research Dr. J.D. Wadate I Dr. Mukul Burghate, Research is a part of any systematic knowledge. It has occupied the realm of human understanding in some form or the other from times immemorial. The thirst for new areas of knowledge and the human urge for solutions to the problems have developed a faculty for search and research and re-research in him/her. Research has now become an integral part of all the areas of human activity. It is in this context, a study Material on introduction to the subject of Business Research Methodology is presented to the students of Post-Graduate M.Com degree. The purpose of this Study Material is to present an introduction to the Research Methodology subject of M.Com. The book contains the syllabus from basics of the subjects going into the intricacies of the subjects. All the concepts have been explained with relevant examples and diagrams to make it interesting for the readers. An attempt is made here by the experts of TMC to assist the students by way of providing Study Material as per the curriculum with non-commercial considerations. However, it is implicit that these are exam-oriented Study Material and students are advised to attend regular lectures in the Institute and utilize reference books available in the library for In-depth knowledge. We owe to many websites and their free contents; we would like to specially acknowledge contents of website www.wikipedia.com and various authors whose writings formed the basis for this book. We acknowledge our thanks to them. At the end we would like to say that there is always a room for improvement in whatever we do. We would appreciate any suggestions regarding this study material from the readers so that the contents can be made more interesting and meaningful. Readers can email their queries and doubts to our authors on tmcnagpur@gmail.com. We shall be glad to help you immediately. |
| discriminant analysis interpretation spss: Applied Statistics II Rebecca M. Warner, 2020-01-14 Rebecca M. Warner’s bestselling Applied Statistics: From Bivariate Through Multivariate Techniques has been split into two volumes for ease of use over a two-course sequence. Applied Statistics II: Multivariable and Multivariate Techniques, Third Edition is a core multivariate statistics text based on chapters from the second half of the original book. The text begins with two new chapters: an introduction to the new statistics, and a chapter on handling outliers and missing values. All chapters on statistical control and multivariable or multivariate analyses from the previous edition are retained (with the moderation chapter heavily revised) and new chapters have been added on structural equation modeling, repeated measures, and on additional statistical techniques. Each chapter includes a complete example, and begins by considering the types of research questions that chapter’s technique can answer, progresses to data screening, and provides screen shots of SPSS menu selections and output, and concludes with sample results sections. By-hand computation is used, where possible, to show how elements of the output are related to each other, and to obtain confidence interval and effect size information when SPSS does not provide this. Datasets are available on the accompanying website. Bundle and Save Applied Statistics II + Applied Statistics I: Basic Bivariate Techniques, Third Edition Bundle Volume I and II ISBN: 978-1-0718-1337-9 An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques + Applied Statistics II Bundle ISBN: 978-1-0718-3618-7 |
| discriminant analysis interpretation spss: IBM SPSS for Introductory Statistics George A. Morgan, Nancy L. Leech, Gene W. Gloeckner, Karen C. Barrett, 2012-09-10 Designed to help students analyze and interpret research data using IBM SPSS, this user-friendly book, written in easy-to-understand language, shows readers how to choose the appropriate statistic based on the design, and to interpret outputs appropriately. The authors prepare readers for all of the steps in the research process: design, entering and checking data, testing assumptions, assessing reliability and validity, computing descriptive and inferential parametric and nonparametric statistics, and writing about outputs. Dialog windows and SPSS syntax, along with the output, are provided. Three realistic data sets, available on the Internet, are used to solve the chapter problems. The new edition features: Updated to IBM SPSS version 20 but the book can also be used with older and newer versions of SPSS. A new chapter (7) including an introduction to Cronbach’s alpha and factor analysis. Updated Web Resources with PowerPoint slides, additional activities/suggestions, and the answers to even-numbered interpretation questions for the instructors, and chapter study guides and outlines and extra SPSS problems for the students. The web resource is located www.routledge.com/9781848729827 . Students, instructors, and individual purchasers can access the data files to accompany the book at www.routledge.com/9781848729827 . IBM SPSS for Introductory Statistics, Fifth Edition provides helpful teaching tools: All of the key IBM SPSS windows needed to perform the analyses. Complete outputs with call-out boxes to highlight key points. Flowcharts and tables to help select appropriate statistics and interpret effect sizes. Interpretation sections and questions help students better understand and interpret the output. Assignments organized the way students proceed when they conduct a research project. Examples of how to write about outputs and make tables in APA format. Helpful appendices on how to get started with SPSS and write research questions. An ideal supplement for courses in either statistics, research methods, or any course in which SPSS is used, such as in departments of psychology, education, and other social and health sciences. This book is also appreciated by researchers interested in using SPSS for their data analysis. |
| discriminant analysis interpretation spss: Doing Research in Psychological Therapies Joel Vos, 2023-09-02 This comprehensive and highly practical ‘how to’ book guides researchers from start to finish through the research process. The easy-to-follow consecutive steps cover: basic academic skills, literature reviews, research aims, selection of quantitative, qualitative or mixed methods, research and ethics proposals, data collection and analysis, and final thesis or report. Supported by decision-making flowcharts, further reading, reflective questions, state-of-the-art trends and templates, this book ensures you produce a sound and coherent research project that fulfils your training and publication requirements. It is the go-to guide for beginning and advanced researchers in counselling, psychotherapy, counselling and clinical psychology, psychiatry and related disciplines. |
| discriminant analysis interpretation spss: Management Research Methodology K. N. Krishnaswamy, Appa Iyer Sivakumar, M. Mathirajan, 2009 The subject of management research methodology is enthralling and complex. A student or a practitioner of management research is beguiled by uncertainties in the search and identification of the research problem, intrigued by the ramifications of research design, and confounded by obstacles in obtaining accurate data and complexities of data analysis. Management Research Methodology: Integration of Principles, Methods and Techniques seeks a balanced treatment of all these aspects and blends problem-solving techniques, creativity aspects, mathematical modelling and qualitative approaches in order to present the subject of Management Research Methodology in a lucid and easily understandable way. |
| discriminant analysis interpretation spss: Hydro-Environmental Analysis James L. Martin, 2013-12-04 Focusing on fundamental principles, Hydro-Environmental Analysis: Freshwater Environments presents in-depth information about freshwater environments and how they are influenced by regulation. It provides a holistic approach, exploring the factors that impact water quality and quantity, and the regulations, policy and management methods that are necessary to maintain this vital resource. It offers a historical viewpoint as well as an overview and foundation of the physical, chemical, and biological characteristics affecting the management of freshwater environments. The book concentrates on broad and general concepts, providing an interdisciplinary foundation. The author covers the methods of measurement and classification; chemical, physical, and biological characteristics; indicators of ecological health; and management and restoration. He also considers common indicators of environmental health; characteristics and operations of regulatory control structures; applicable laws and regulations; and restoration methods. The text delves into rivers and streams in the first half and lakes and reservoirs in the second half. Each section centers on the characteristics of those systems and methods of classification, and then moves on to discuss the physical, chemical, and biological characteristics of each. In the section on lakes and reservoirs, it examines the characteristics and operations of regulatory structures, and presents the methods commonly used to assess the environmental health or integrity of these water bodies. It also introduces considerations for restoration, and presents two unique aquatic environments: wetlands and reservoir tailwaters. Written from an engineering perspective, the book is an ideal introduction to the aquatic and limnological sciences for students of environmental science, as well as students of environmental engineering. It also serves as a reference for engineers and scientists involved in the management, regulation, or restoration of freshwater environments. |
| discriminant analysis interpretation spss: Applied MANOVA and Discriminant Analysis Carl J. Huberty, Stephen Olejnik, 2006-05-12 A complete introduction to discriminant analysis--extensively revised, expanded, and updated This Second Edition of the classic book, Applied Discriminant Analysis, reflects and references current usage with its new title, Applied MANOVA and Discriminant Analysis. Thoroughly updated and revised, this book continues to be essential for any researcher or student needing to learn to speak, read, and write about discriminant analysis as well as develop a philosophy of empirical research and data analysis. Its thorough introduction to the application of discriminant analysis is unparalleled. Offering the most up-to-date computer applications, references, terms, and real-life research examples, the Second Edition also includes new discussions of MANOVA, descriptive discriminant analysis, and predictive discriminant analysis. Newer SAS macros are included, and graphical software with data sets and programs are provided on the book's related Web site. The book features: Detailed discussions of multivariate analysis of variance and covariance An increased number of chapter exercises along with selected answers Analyses of data obtained via a repeated measures design A new chapter on analyses related to predictive discriminant analysis Basic SPSS(r) and SAS(r) computer syntax and output integrated throughout the book Applied MANOVA and Discriminant Analysis enables the reader to become aware of various types of research questions using MANOVA and discriminant analysis; to learn the meaning of this field's concepts and terms; and to be able to design a study that uses discriminant analysis through topics such as one-factor MANOVA/DDA, assessing and describing MANOVA effects, and deleting and ordering variables. |
| discriminant analysis interpretation spss: Six Sigma and Beyond D.H. Stamatis, 2002-08-28 Researchers and professionals in all walks of life need to use the many tools offered by the statistical world, but often do not have the necessary experience in both concept and application. No matter what your profession, sooner or later numbers need to be crunched, and often you need to understand how to do it, and why it is important. Quality c |
| discriminant analysis interpretation spss: Discriminant Analysis and Statistical Pattern Recognition Geoffrey J. McLachlan, 2005-02-25 The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field. –SciTech Book News . . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition. –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references. |
| discriminant analysis interpretation spss: Exploratory Multivariate Analysis in Archaeology M. J. Baxter, 2015-12-31 This volume presents four techniques of multivariate analysis commonly used by archaeologists (principal component analysis, correspondence analysis, cluster analysis, and discriminant analysis). Employing ordinary language and real data sets, and including extensive literature reviews, the book illustrates how these statistical techniques can be applied to specific archaeological questions. A new introduction by the author updates his discussion in light of subsequent developments in the field of quantitative archaeology. Originally published by Edinburgh University Press in 1994. |
| discriminant analysis interpretation spss: Acoustical Imaging Michael P. André, Joie P. Jones, Hua Lee, 2011-07-24 In the course of the years the volumes in the Acoustical Imaging Series have developed to become well-known and appreciated reference works. Offering both a broad perspective on the state of the art in the field as well as an in-depth look at its leading edge research, this Volume 30 in the Series contains again an excellent collection of contributions, presented in five major categories: |
| discriminant analysis interpretation spss: InfoWorld , 1992-09-21 InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects. |
| discriminant analysis interpretation spss: Business Research Methods Naval Bajpai, Business Research Methods, 2e, provides students with the knowledge, understanding and necessary skills to conduct business research. The reader is taken step-by-step through a range of contemporary research methods, while numerous worked examples and real-life case studies enable students to relate with the context and thus grasp concepts effectively. Keeping in mind the developments in the subject area and necessary feedback from the users of this book, the latest edition has been extensively revised to include the necessary updates. The revision has been carried out in three ways: (i) by adding a few topics in existing chapters, (ii) by restructuring chapters pertaining to multivariate techniques, and (iii) by including a new chapter - Chapter 20: Confirmatory Factor Analysis, Structural Equation Modelling and Path Analysis. |
SPSS Discriminant Function Analysis - kharazmi-statistics.ir
Discriminant Function Analysis SPSS output: test of homogeneity of covariance matrices 1. Box's M test tests the assumption of homogeneity of covariance matrices. This test is very sensitive …
MULTIPLE DISCRIMINANT ANALYSIS
• The primary objective of multiple discriminant analysis are to understand group differences and to predict the likelihood that an entity (individual or object) will belong to a particular class or …
A Student’s Guide to Interpreting SPSS Output for Basic …
These slides give examples of SPSS output with notes about interpretation. All analyses were conducted using the Family Exchanges Study, Wave 1 (target dataset)1 from ICPSR. The …
UNIT 10 DISCRIMINANT ANALYSIS AND LOGISTIC …
In this unit, we will discuss two methods of multivariate analysis: discriminant analysis and logistic regression. Discriminant analysis is useful in situations where a total sample could be …
LESSON 2: DISCRIMINANT ANALYSIS - ResearchGate
The purpose of discriminant analysis is to obtain a model to predict a single qualitative variable from one or more independent variable(s). In most cases the dependent variable consists of …
Discriminant analysis: An illustrated example
This paper demonstrates an illustrated approach in presenting how the discriminant analysis can be carried out and how the output can be interpreted using knowledge sharing in an …
Discriminant Analysis Interpretation Spss - mdghs.com
Mastering the interpretation of discriminant analysis in SPSS empowers researchers to extract valuable insights from their data. By understanding the discriminant function coefficients, …
Discriminant Function Analysis Spss (book)
capabilities, step-by-step procedures, interpretation of results, and common pitfalls to avoid. By the end, you'll be equipped to confidently perform and interpret DFA in SPSS, unlocking …
Demonstration of 2-Group Linear Discriminant Function Analysis
There are two sets of values that are routinely used to interpret ldfs. The standardized ldf coefficients are just that, the ß weights we use with participant’s standardized predictor scores …
Factor and Discriminant Analysis - MeasuringU
Together we’ll conduct a stepwise discriminant analysis with the five SUPR-Q variables to develop a classification model for the four-cluster designations captured in the SPSS data file as CLU4_1.
Discriminant Analysis Interpretation Spss
Mastering the interpretation of discriminant analysis in SPSS empowers researchers to extract valuable insights from their data. By understanding the discriminant function coefficients, …
Chapter 6 Discriminant Analyses SPSS - Discriminant Analyses
Discriminant Analysis is used primarily to predict membership in two or more mutually exclusive groups. This menu selection opens the following dialog box: First enter the grouping variable …
Discriminant Analysis - Statpower
But first, let’s perform the analysis using the more general approach employed by SPSS. SPSS can report a linear discriminant function for each group, as in Equations (14)–(15).
Research Design - - Topic 23 Discriminant Function Analysis
An Example Using SPSS Discriminant To demonstrate the similarities and differences between single factor multivariate analysis of variance and discriminant function
Discriminant Analysis Interpretation Spss
Mastering the interpretation of discriminant analysis in SPSS empowers researchers to extract valuable insights from their data. By understanding the discriminant function coefficients, …
Chapter 25 Discriminant Analysis - ResearchGate
How to use SPSS to perform discriminant analysis. How to interpret the SPSS print out of discriminant analysis. This chapter introduces another extension of regression where the...
Chapter 12 Application of Discriminant Analysis: For ... - Springer
† Understand the steps involved in using SPSS for discriminant analysis. † To interpret the output obtained in discriminant analysis. † Explain the procedure in developing the decision rule …
Discriminant analysis is a technique for analyzing data when …
The objectives of discriminant analysis are as follows: 1 Development of discriminant functions, or linear combinations of the predictor or independent variables, that best discriminate between …
Biostatistics 303. Discriminant analysis - Paulo Gentil
Discriminant analysis (DA) was the traditional statistical technique used for differentiating groups (categorical dependent variable) when the independent variables were quantitative. Consider …
Discriminant analysis: An illustrated example - Academic …
Discriminant or discriminant function analysis is a parametric technique to determine which weightings of quantitative variables or predictors best discriminate between 2 or more than 2 …
SPSS Discriminant Function Analysis - kharazmi-statisti…
Discriminant Function Analysis SPSS output: test of homogeneity of covariance matrices 1. Box's M test …
MULTIPLE DISCRIMINANT ANALYSIS - grandacademic…
• The primary objective of multiple discriminant analysis are to understand group differences and to predict the …
A Student’s Guide to Interpreting SPSS Output …
These slides give examples of SPSS output with notes about interpretation. All analyses were conducted using …
UNIT 10 DISCRIMINANT ANALYSIS AND LOGISTIC R…
In this unit, we will discuss two methods of multivariate analysis: discriminant analysis and logistic …
LESSON 2: DISCRIMINANT ANALYSIS - ResearchGate
The purpose of discriminant analysis is to obtain a model to predict a single qualitative variable from one or …
