This innovative research design text will help you make informed choices when carrying out your research project. Covering both qualitative and quantitative approaches, and with examples drawn from a wide range of social science disciplines, the authors explain what is at stake when choosing a research design, and discuss the trade-offs that researchers have to make when considering issues such as: - causality - categories and classification - heterogeneity - interdependence - time This book will appeal to students and researchers looking for an in-depth understanding of research design issues to help them design their projects in a thoughtful and responsible way.

This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied.

This book is a review and high-yield reference on the clinical molecular diagnostics of malignant neoplasms. It aims to address the practical questions frequently encountered in the molecular oncology practice, as well as key points and pitfalls in the clinical interpretation of molecular tests in guiding precision cancer management. The text uses a Q&A format and case presentations, with emphasis on understanding the molecular test methods, diagnosis, classification, risk assessment and clinical correlation. Starting with an update on the molecular biology of cancer, the book focuses on the topics related to molecular diagnostics and genetics-based precision oncology. Separate chapters are dedicated to discussion of the bioinformatics for the analysis of genetic/genomic data generated from molecular assays, and quality control (QC)/quality assurance (QA) programs in the clinical laboratories; both are critical in producing high quality results for clinical care of cancer patients. These are followed by organ system-based reviews and discussions on the molecular genetic abnormalities and related tests covering diverse types of common to rare malignant neoplasms. This book also provides up-to-date knowledge related to malignant neoplasms, discusses the established as well as evolving requirements for pathologic diagnosis of these malignancies. It also discusses the cost effective utilization of molecular tests in clinical oncology. Written by experts in the field, Practical Oncologic Molecular Pathology serves as a valuable reference for practicing pathologists, fellows, residents and other health care professionals.

Computer access is the only way to retrieve up-to-date sequences and this book shows researchers puzzled by the maze of URLs, sites, and searches how to use internet technology to find and analyze genetic data. The book describes the different types of databases, how to use a specific database to find a sequence that you need, and how to analyze the data to compare it with your own work. The content also covers sequence phenotype, mutation, and genetic linkage databases; simple repetitive DNA sequences; gene feature identification; and prediction of structure and function of proteins from sequence information. This book will be invaluable to those starting a career in life sciences research as well as to established researchers wishing to make full use of available resources. - Describes a wide range of databases: DNA, RNA, protein, pathways, and gene expression - Enables readers to access the information they need from databases on the web - Includes a directory of URLs for easy reference - Invaluable for those starting a career in life sciences research and also for established researchers wishing to make full use of available resources

Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Randall E. Schumacker’s comprehensive book describes in detail the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Learning Statistics Using R covers data input from vectors, arrays, matrices and data frames, as well as the input of data sets from SPSS, SAS, STATA and other software packages. Schumacker’s text provides the freedom to effectively calculate, manipulate, and graphically display data, using R, on different computer operating systems without the expense of commercial software. Learning Statistics Using R places statistics within the framework of conducting research, where statistical research hypotheses can be directly addressed. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers′ understanding of statistics through statistical computing and modeling.

Mathematics is the music of science, and real analysis is the Bach of mathematics. There are many other foolish things I could say about the subject of this book, but the foregoing will give the reader an idea of where my heart lies. The present book was written to support a first course in real analysis, normally taken after a year of elementary calculus. Real analysis is, roughly speaking, the modern setting for Calculus, "real" alluding to the field of real numbers that underlies it all. At center stage are functions, defined and taking values in sets of real numbers or in sets (the plane, 3-space, etc.) readily derived from the real numbers; a first course in real analysis traditionally places the emphasis on real-valued functions defined on sets of real numbers. The agenda for the course: (1) start with the axioms for the field ofreal numbers, (2) build, in one semester and with appropriate rigor, the foun dations of calculus (including the "Fundamental Theorem"), and, along the way, (3) develop those skills and attitudes that enable us to continue learning mathematics on our own. Three decades of experience with the exercise have not diminished my astonishment that it can be done.