Beyond Anova

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.

Statistics is required coursework within most teacher certification programs. Beyond the Numbers presents a nonthreatening, practical approach to statistics, providing step-by-step instructions for understanding and implementing the essential components of the subject.The basic and understandable explanations in Beyond the Numbers break down complex statistical processes to simple arithmetic computations that can be applied with the confidence that accompanies understanding.

This volume addresses design improvement from the perspective of prevention by introducing readers to the tools of the Six Sigma design process. The author discusses the issues of designing for Six Sigma, covering the topics that any Shogun Six Sigma Master must be familiar with: customer satisfaction, quality function deployment, benchmarking, sys

Noted for its model-comparison approach and unified framework based on the general linear model (GLM), this classic text provides readers with a greater understanding of a variety of statistical procedures including analysis of variance (ANOVA) and regression.

The proceedings of the International Symposium on Open, Distance, and E-Learning (ISODEL 2021) share ideas, either research results or literature reviews, on distance education, media, and education in the digital era. Some recent issues consist of innovative education in the digital era, new media Industry 4.0, Digital Education Transformation, Character Building, Vocational Education 4.0, and Preserving Future Children Characters and Culture. It is expected that the proceedings will provide new insights to the knowledge and practice of education and education technology research. Therefore, such parties involved in education research such as academics, practitioners, business leaders, and others will benefit from the contents of the proceedings.

Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/

The juvenile, or two-year-old, racing careers of Colin, Man o War, Ruffian and Landaluce provide the foundation and focus for discussing the question of thoroughbred greatness and its measure. These four thoroughbreds were arguably the best juvenile runners of the twentieth century. Close on their hooves, pun intended, however, were the colts Sysonby and Secretariat and the fillies First Flight, La Prevoyante and Personal Ensign. The latter five runners are honorably mentioned and also compared in the book. As in The Greatest Horse of All: A Controversy Examined, basic statistics are used informally to provide readers a basis for their own studies in thoroughbred data comparison and evaluation. The author realizes that many people avoid mathematical ideas like the plague. Therefore, he has minimized statistical usage to its most common elements, and he explains these thoroughly for the uninitiated as the book progresses. Only two of the ten chapters use statistics to any degree. The text also includes seven figures and two tables to aid in understanding the statistical concepts. If one feels remotely comfortable with eight-grade mathematics concepts, one will have no problem with this material. Relative to the statistical comparisons, two novel concepts are discussed. These pertain to addressing the so-called era effect. Many racing fans continue to argue that horses from different eras cannot justly be compared. A strong case against this argument is presented from at least two standpoints. First, a device is described and suggested to scientifically test and compare the true relative speeds of two racing surfaces. Second, an inverse use of the well-known t test for comparing the differences between two or more data sets is presented. The text demonstrates how using this inverse test can equitably adjust earlier era data so that it may be fairly compared with later era data.