Author: Rebecca M. Warner
Release Date: 2012-04-10
Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.
Author: Douglas C. Montgomery
Publisher: John Wiley & Sons
Release Date: 2010-03-22
Genre: Technology & Engineering
Montgomery and Runger's bestselling engineering statistics text provides a practical approach oriented to engineering as well as chemical and physical sciences. By providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers. With a focus on how statistical tools are integrated into the engineering problem-solving process, all major aspects of engineering statistics are covered. Developed with sponsorship from the National Science Foundation, this text incorporates many insights from the authors' teaching experience along with feedback from numerous adopters of previous editions.
Author: Rebecca M. Warner
Release Date: 2008
With an approach that does not require formal mathematics (equations are accompanied by verbal explanations), this textbook provides a clear introduction to widely used topics in multivariate statistics, including Multiple Regression, Discriminant Analysis, MANOVA, Factor Analysis, and Binary Logistic Regression. Each chapter presents a complete empirical research example to illustrate the application of a specific method, such as Multiple Regression. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.
Author: Rupert G. Miller, Jr.
Publisher: CRC Press
Release Date: 1997-01-01
Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of "real world data," Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator. This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests. Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis.
Author: Dennis E. Hinkle
Publisher: Houghton Mifflin College Division
Release Date: 2003
This introductory text provides students with a conceptual understanding of basic statistical procedures, as well as the computational skills needed to complete them. The clear presentation, accessible language, and step-by-step instruction make it easy for students from a variety of social science disciplines to grasp the material. The scenarios presented in chapter exercises span the curriculum, from political science to marketing, so that students make a connection between their own area of interest and the study of statistics. Unique coverage focuses on concepts critical to understanding current statistical research such as power and sample size, multiple comparison tests, multiple regression, and analysis of covariance. Additional SPSS coverage throughout the text includes computer printouts and expanded discussion of their contents in interpreting the results of sample exercises.
Author: Olive Jean Dunn
Publisher: John Wiley & Sons Inc
Release Date: 1987-05-11
Descriptive statistics. Statistical inference: populations and samples. Inference from a single sample. Samples from two populations. One-way analysis of variance: fixed effects model. Hierarchical or nested design. Two-way analysis of variance: fixed effects model. Three-way analysis of variance: fixed effects model. Factorial designs with each factor at two levels. Variable effects models. Repeated measure designs. Linear regression and correlation. Multiple regression: the fixed X model. Multiple regression and correlation analysis. Analysis of covariance. Data screening.
Author: W.N. Venables
Publisher: Springer Science & Business Media
Release Date: 2013-03-09
A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.
Author: Mohammad Ahsanullah
Publisher: Nova Publishers
Release Date: 2003-01-01
Computers have taken a permanent place in almost every human endeavour in the last 20 years. This infiltration requires a learning process on the part of the people utilising them and realising where and how they can be best used beyond the basic and obvious applications. Statistics is an example of their application in many diverse fields to reach conclusions and make projections never before possible. Beyond this, applied statistics is rapidly becoming not only an instrument, but an integral part of the advance of knowledge. There are many fields such as medicine, biology, weather prediction, military planning, and many others where the statistical studies are essential before the next step can be taken. This book gathers together the latest research in this dynamic and link field.
As the first book ever published for public administration statistics courses, APPLIED STATISTICS FOR PUBLIC AND NONPROFIT ADMINISTRATION makes a difficult subject accessible to students and practitioners of public administration and to non-profit studies who have little background in statistics or research methods. Steeped in experience and practice, this landmark text remains the first and best in research methods and statistics for students and practitioners in public-and nonprofit-administration. All statistical techniques used by public administration professionals are covered, and all examples in the text relate to public administration and the nonprofit sector. Avoiding jargon and formula, this text uses a step-by-step approach that facilitates student learning. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Author: Joaquim P. Marques de Sá
Publisher: Springer Science & Business Media
Release Date: 2007-05-28
Intended for anyone needing to apply statistical analysis to a large variety of science and engineering problems, this book shows how to use SPSS, MATLAB, STATISTICA and R for data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. The 2nd edition includes the R language, a new section on bootstrap estimation methods and an improved treatment of tree classifiers, plus additional examples and exercises.
Author: Margaret Lewis
Release Date: 2012-11-12
Genre: Business & Economics
This book is an undergraduate text that introduces students to commonly-used statistical methods in economics. Using examples based on contemporary economic issues and readily-available data, it not only explains the mechanics of the various methods, it also guides students to connect statistical results to detailed economic interpretations. Because the goal is for students to be able to apply the statistical methods presented, online sources for economic data and directions for performing each task in Excel are also included.