This expanded and updated Third Edition of Gopal K. Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test's purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example, and the numerical calculation. 100 Statistical Tests, Third Edition is the one indispensable guide for users of statistical materials and consumers of statistical information at all levels and across all disciplines.
The student and researcher are faced with a vast array of statistical tests, and this new edition of the bestselling 100 Statistical Tests covers all the most commonly used tests with information on how to calculate and interpret results with sample datasets. The new version simplifies and clarifies a number of tests and the information on the limitations of tests has been expanded. Praise for the First Edition: `Every person who does statistical testing should have a copy of this reasonably priced book' - Journal of Quality Technology `Strongly recommended' - British Journal of Educational Psychology `I cannot praise this book too
As the number of tests has increased, so has the pressing need for a single source of reference. Bringing together the hundred most commonly used tests, this volume provides just such an indispensable aid for student and statistician alike. An introduction discusses the principles of hypothesis-testing. Examples of the procedure for selected tests follow, illustrating statistical method in practice. The purpose of each test is summarized and a classification chart identifies their interconnections and contexts of use. The bulk of the book consists of clear, concise outlines of the objective, method, strengths and limitations of each test, giving sample data. All the relevant tables of critical values are included. 100 Statistical Tests is an invaluable addition to the bookshelf of anyone working with applied statistics and quantitative methodologies throughout the social sciences, business and management.
100 Statistical Tests in R is designed to give you rapid access to one hundred of the most popular statistical tests. It shows you, step by step, how to carry out these tests in the free and popular R statistical package. The book was created for the applied researcher whose primary focus is on their subject matter rather than mathematical lemmas or statistical theory. Step by step examples of each test are clearly described, and can be typed directly into R as printed on the page. To accelerate your research ideas, over three hundred applications of statistical tests across engineering, science, and the social sciences are discussed.
Modern DNA microarray technologies have evolved over the past 25 years to the point where it is now possible to take many million measurements from a single experiment. These two volumes, Parts A & B in the Methods in Enzymology series provide methods that will shepard any molecular biologist through the process of planning, performing, and publishing microarray results. Part A starts with an overview of a number of microarray platforms, both commercial and academically produced and includes wet bench protocols for performing traditional expression analysis and derivative techniques such as detection of transcription factor occupancy and chromatin status. Wet-bench protocols and troubleshooting techniques continue into Part B. These techniques are well rooted in traditional molecular biology and while they require traditional care, a researcher that can reproducibly generate beautiful Northern or Southern blots should have no difficulty generating beautiful array hybridizations. Data management is a more recent problem for most biologists. The bulk of Part B provides a range of techniques for data handling. This includes critical issues, from normalization within and between arrays, to uploading your results to the public repositories for array data, and how to integrate data from multiple sources. There are chapters in Part B for both the debutant and the expert bioinformatician. Provides an overview of platforms Includes experimental design and wet bench protocols Presents statistical and data analysis methods, array databases, data visualization and meta analysis
Do you find statistics overwhelming and confusing? Have you ever wished for someone to explain the basics in a clear and easy-to-follow style? This accessible textbook gives a step-by-step introduction to all the topics covered in introductory statistics courses for the behavioural sciences, with plenty of examples discussed in depth, based on real psychology experiments utilising the statistical techniques described. Advanced sections are also provided, for those who want to learn a particular topic in more depth. Statistics for the Behavioural Sciences: An Introduction begins with an introduction to the basic concepts, before providing a detailed explanation of basic statistical tests and concepts such as descriptive statistics, probability, the binomial distribution, continuous random variables, the normal distribution, the Chi-Square distribution, the analysis of categorical data, t-tests, correlation and regression. This timely and highly readable text will be invaluable to undergraduate students of psychology, and students of research methods courses in related disciplines, as well as anyone with an interest in the basic concepts and tests associated with statistics in the behavioural sciences.
Struggling to do a project or dissertation, evaluate published research or conduct your own research? Help is at hand with this 5th edition of Research Methods for Clinical Therapists, which explains, in a clear and simple manner, how to evaluate existing research and how to conduct your own research. Aimed at undergraduate and postgraduate students, as well as the practising health care professional, the focus of the text is the design and analysis of experimental studies. These are vital to the effectiveness studies that are central to the work of the healthcare professional. Specific examples from different areas of healthcare are used to explain the core research concepts and relate them to clinical situations. Statistical theory and jargon are kept to a minimum. 'Key concept' boxes to explain technical research terms Activities and exercises (with answers provided in an appendix) to reinforce learning Sample critique of a published research article Comprehensive coverage of the key components of a robust research study Explanation of basic mathematical concepts Extended section on calculating sample sizes Guidelines on the preparation of posters Calculation of Inter-rater reliability measures, including Cohen’s Kappa, ICC (interclass correlation) and Bland-Altman graphs of inter-rater agreement Introduction to Receiver Operating Characteristics, for use in screening and diagnostic testing against gold-standards The Thurstone Paired Comparison Technique, valuable in capturing the user voice on a variety of service planning, design and development issues Undertaking Systematic Reviews Relevant further reading for each chapter to support readers in their work.
Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in "ordinal" data. As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Non-parametric methods have many popular applications, and are widely used in research in the fields of the behavioral sciences and biomedicine. This is a textbook on non-parametric statistics for applied research. The authors propose to use a realistic yet mostly fictional situation and series of dialogues to illustrate in detail the statistical processes required to complete data analysis. This book draws on a readers existing elementary knowledge of statistical analyses to broaden his/her research capabilities. The material within the book is covered in such a way that someone with a very limited knowledge of statistics would be able to read and understand the concepts detailed in the text. The “real world” scenario to be presented involves a multidisciplinary team of behavioral, medical, crime analysis, and policy analysis professionals work together to answer specific empirical questions regarding real-world applied problems. The reader is introduced to the team and the data set, and through the course of the text follows the team as they progress through the decision making process of narrowing the data and the research questions to answer the applied problem. In this way, abstract statistical concepts are translated into concrete and specific language. This text uses one data set from which all examples are taken. This is radically different from other statistics books which provide a varied array of examples and data sets. Using only one data set facilitates reader-directed teaching and learning by providing multiple research questions which are integrated rather than using disparate examples and completely unrelated research questions and data.
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.
The Barnacle Goose, a distinctive, handsome black-and-white bird, gets its name from a mediaeval myth that the birds hatched from barnacles – how else to explain their sudden appearance each autumn in northern Britain? We now know, of course, that the birds migrate from Arctic Russia, Norway and Svalbard to winter throughout northern Europe. This book represents a culmination of more than 25 years of Barnacle Goose research. It represents the story of one of Europe's most celebrated long-term behavioral studies, detailing the lives of these social and sociable birds. Chapters include sections on pair formation and bonding, family and population dynamics, brood parasitism, food and feeding, size and shape in different populations, life cycle, survivorship, dispersal, migration, and conservation, with particular regard to climate change. It is a rigorous and thorough examination of the lives of these birds, in fine Poyser tradition.