Language : English
Published : 2015-11-25
Pages : 814
Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and IBM’s SPSS, Sixth Edition 6th Edition
Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: * NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure * NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this “newer” procedure and how it can be used in conventional and multilevel settings * NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles * NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data * Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results * NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach * Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) * A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises). Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.
About the Author
Keenan Pituch is Associate Professor in the Quantitative Methods Area of the Department of Educational Psychology at the University of Texas at Austin. James P Stevens is Professor Emeritus at University of Cincinatti.
Navidi/Monk, Essential Statistics was developed around three central themes – Clarity, Quality, and Accuracy. These central themes were born out of extensive market research and feedback from statistics instructors across the country. The authors paid close attention to how material is presented to students, ensuring that the content in the text is very clear, concise, and digestible. High quality exercises, examples and integration of technology are important aspects of an Introductory Statistics text. The authors have provided robust exercise sets that range in difficulty. They have also focused keen attention to ensure that examples provide clear instruction to students. Technology is integrated throughout the text, providing students examples of how to use the TI-83 Plus and TI-84 Plus Graphing Calculators, Microsoft Excel and Minitab. The accuracy of Elementary Statistics was a foundational principle always on the minds of the authors. While this certainly pertains to all aspects of the text, the authors also exhausted energy in ensuring the supplements have been developed to fit cohesively with the text.
Praise for the First Edition
“. . . a readable, comprehensive volume that . . . belongs on the desk, close at hand, of any serious researcher or practitioner.” —Mathematical Geosciences
The state of the art in geostatistics
Geostatistical models and techniques such as kriging and stochastic multi-realizations exploit spatial correlations to evaluate natural resources, help optimize their development, and address environmental issues related to air and water quality, soil pollution, and forestry. Geostatistics: Modeling Spatial Uncertainty, Second Edition presents a comprehensive, up-to-date reference on the topic, now featuring the latest developments in the field.
The authors explain both the theory and applications of geostatistics through a unified treatment that emphasizes methodology. Key topics that are the foundation of geostatistics are explored in-depth, including stationary and nonstationary models; linear and nonlinear methods; change of support; multivariate approaches; and conditional simulations. The Second Edition highlights the growing number of applications of geostatistical methods and discusses three key areas of growth in the field:
- New results and methods, including kriging very large datasets; kriging with outliers; nonse??parable space-time covariances; multipoint simulations; pluri-gaussian simulations; gradual deformation; and extreme value geostatistics
- Newly formed connections between geostatistics and other approaches such as radial basis functions, Gaussian Markov random fields, and data assimilation
- New perspectives on topics such as collocated cokriging, kriging with an external drift, discrete Gaussian change-of-support models, and simulation algorithms
Geostatistics, Second Edition is an excellent book for courses on the topic at the graduate level. It also serves as an invaluable reference for earth scientists, mining and petroleum engineers, geophysicists, and environmental statisticians who collect and analyze data in their everyday work.
From the Back Cover
A novel, practical approach to modeling spatial uncertainty.
This book deals with statistical models used to describe natural variables distributed in space or in time and space. It takes a practical, unified approach to geostatistics-integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This unique approach facilitates realistic modeling that accounts for the complexity of natural phenomena and helps solve economic and development problems-in mining, oil exploration, environmental engineering, and other real-world situations involving spatial uncertainty.
Up-to-date, comprehensive, and well-written, Geostatistics: Modeling Spatial Uncertainty explains both theory and applications, covers many useful topics, and offers a wealth of new insights for nonstatisticians and seasoned professionals alike. This volume:
* Reviews the most up-to-date geostatistical methods and the types of problems they address.
* Emphasizes the statistical methodologies employed in spatial estimation.
* Presents simulation techniques and digital models of uncertainty.
* Features more than 150 figures and many concrete examples throughout the text.
* Includes extensive footnoting as well as a thorough bibliography.
Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate-level courses in related subjects. –This text refers to an out of print or unavailable edition of this title.
This text is adapted from Jessica Utts and Robert Heckard, it’s best-selling general introductory statistics text, Mind on Statistics. It emphasises the conceptual development of statistical ideas and seeks to find meaning in data. This local adaptation retains the conversational approach of the original text, with real examples and case studies of appeal and interest to Australian and New Zealand students. The revised structure and relevant examples motivate students and guide them through the statistical process of tackling problems, planning and data collection, analysing and interpreting information and finding solutions.
UNDERSTANDABLE STATISTICS: CONCEPTS AND METHODS, Eleventh Edition, is a thorough yet accessible program designed to help students overcome their apprehensions about statistics. The authors provide clear guidance and informal advice while showing students the links between statistics and the world. To reinforce this approach, the book integrates real-life data from a variety of sources, including journals, periodicals, newspapers, and the Internet. The eleventh edition continues to address the importance of developing students’ critical-thinking and statistical literacy skills through special features and exercises throughout the text. The use of graphing calculators, Excel, MINITAB, and SPSS is covered although not required. Extensive technology resources include an algorithmic Test Bank and lecture slides, along with interactive online resources and a market-leading DVD series designed to provide reinforcement for students and support for instructors.