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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 and has been updated with the SPSS statistical package for Windows. New to the Second Edition Three new chapters on multiple discriminant analysis, logistic regression, and canonical correlation New section on how to deal with missing data Coverage of tests of assumptions, such as linearity, outliers, normality, homogeneity of variance-covariance matrices, and multicollinearity Discussions of the calculation of Type I error and the procedure for testing statistical significance between two correlation coefficients obtained from two samples Expanded coverage of factor analysis, path analysis (test of the mediation hypothesis), and structural equation modeling Suitable for both newcomers and seasoned researchers in the social sciences, the handbook offers a clear guide to selecting the right statistical test, executing a wide range of univariate and multivariate statistical tests via the Windows and syntax methods, and interpreting the output results. The SPSS syntax files used for executing the statistical tests can be found in the appendix. Data sets employed in the examples are available on the book’s CRC Press web page.
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
Many statistics texts tend to focus more on the theory and mathematics underlying statistical tests than on their applications and interpretation. This can leave readers with little understanding of how to apply statistical tests or how to interpret their findings. While the SPSS statistical software has done much to alleviate the frustrations of s
The book is a study of intra-urban inequality in quality of life (QOL) in Aizawl city. The main objectives of the study include analysis of processes and patterns of social differentiation along the three-dimensional space of Aizawl city as well as analysis of spatial inequality in QOL at the lowest administrative structure of the city. An investigation into spatial pattern of residential differentiation was done at both horizontal and vertical spaces. Spatial variation in well-being of residents of Aizawl city and the quality of their immediate environment was also studied by taking both objective and subjective indicators. The study employed a number of descriptive, inferential and multivariate statistical techniques including correlation, factor analysis, principal component analysis, cluster analysis and spatial autocorrelation methods like Moran’s I and Local Indicators of Spatial Association (LISA). Mapping techniques and graphical methods like Choropleth map, histogram and line graph were also used. With the help of factor analysis, the social space of Aizawl city was found to be differentiated along socio-economic status, family status, household size status, workers status and ethnic status. The most important factor determining residential differentiation was socio-economic status. Choropleth map of factor scores reveals that the inner city localities were dominated by high socio-economic class while poorer people dominated the peripheries. Non-local ethnic minorities were few but concentrated in some adjoining peripheral localities as well as in inner city localities which have been inhabited by their ancestors since the colonial period. Vertical pattern of residential differentiation was also analyzed by taking income variable as a proxy of socio-economic status. Multi-storey buildings in Aizawl city were co-inhabited by both richer people and poorer people. The richer people were found at the top floors while the poorer people occupied the basement floors. Normally, the owners of the buildings were found at the top floors while the basement floors were dominated by the renters. Spatial variation in QOL was measured with the help of principal component analysis as a weighting technique by taking variables pertaining to both objective and subjective QOL dimensions. The values of composite QOL index showed that the central localities have scored better than their peripheral counterparts. Correlation analysis of the relationship between objective indicators and subjective indicators provided a low positive value indicating the absence of relationship between the two dimensions of quality of life. Spatial autocorrelation analysis was also performed to see the pattern of clustering of spatially weighted QOL variables across Local Councils. With the help of Global Moran’s I, spatial clusters and spatial outliers were observed for objective dimension of QOL within the study area. The value of Moran’s I was found to be insignificant for subjective QOL dimension indicating the absence of significant pattern of clustering. The study also identified 7 social areas of Aizawl city on the basis of factor scores and composite scores of QOL variables calculated for all Local Councils. The identification of clusters was taken out with the help of hierarchical clustering method of cluster analysis. These clusters were labeled appropriate names and their characteristics were described in detail. The thesis concluded with recommendation of designating these social areas as ‘social development planning zones’ for obtaining inclusive development.
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.
This book will help you gain a master of business administration (MBA) degree. Think you’ve got what it takes to become a future leader? An MBA could help you achieve those goals. Intensive, competitive and highly respected, the Master of Business Administration (MBA) is an elite professional qualification. This book provides best reports with good grades. Reading the papers, you can get a sense of how to write a good paper to get good grades. This is a book that tells you how to get good grades on MBA courses in the U.S. For the MBA course, students have to take a total of 36 credits. Each class is worth 3 credits and the students should take 12 classes. It's a series of 12 books, one book for each subject. This book is a collection of best answers for the "Applied Data Analysis" subject.
The third edition of Research Methods for Political Science retains its effective approach to helping students learn what to research, why to research and how to research. The text integrates both quantitative and qualitative approaches to research in one volume and covers such important topics as research design, specifying research problems, designing questionnaires and writing questions, designing and carrying out qualitative research and analyzing both quantitative and qualitative research data. Heavily illustrated, classroom tested, exceptionally readable and engaging, the text presents statistical methods in a conversational tone to help students surmount "math phobia." Updates to this new edition include: Research topics chapters have been upgraded and expanded. Two mixed methods design chapters have been added. A new chapter on hermeneutic analysis designs and research with large data sets. The chapter on multivariate statistics has been expanded, with an expanded discussion on logistic regression. Tools on how to prepare and present research findings are now featured in the appendix, allowing instructors more flexibility when teaching their courses. Research Methods for Political Science will give students the confidence and knowledge they need to understand the methods and basics skills for data collection, presentation and analysis.
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. Pays equal attention to qualitative and quantitative approaches, and is the only book for Public Administration research methods with a dedicated, 4-chapter section on mixed methodologies, exploring fundamentals, research design, data collection, and analyzing and interpreting findings. Contains a new, dedicated chapter on Big Data research, all new exhibits and examples throughout the book, a new companion website to accompany the book containing PowerPoint slides for each chapter, and new exhibits, tables, figures, and exercises, as well as key terms and discussion questions at the end of each chapter. As with past editions, the 4e will be beloved by student and professors alike for its exceptional clarity, accessibility, and plentiful illustrations.
Using a conceptual, non-mathematical approach, the updated Third Edition 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.
This book takes an in-depth look at consumer behavior in the context of multichannel commerce and explores how the convergence of physical and electronic channels influences consumer decision-making in a multichannel environment. In this regard, it goes far beyond explaining choices between online and offline sales channels, instead providing insights into how the interplay between different channel types is valued by different consumer types and for different products. The book extends previous conceptualizations of multichannel commerce to reflect and incorporate recent technological advances. The results provide valuable guidelines on how, why and when multichannel integration services can be exploited by classical retailers, helping them to compete with their purely online competitors on the internet.