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The introduction to statistics that psychology students can't afford to be without Understanding statistics is a requirement for obtaining and making the most of a degree in psychology, a fact of life that often takes first year psychology students by surprise. Filled with jargon-free explanations and real-life examples, Psychology Statistics For Dummies makes the often-confusing world of statistics a lot less baffling, and provides you with the step-by-step instructions necessary for carrying out data analysis. Psychology Statistics For Dummies: Serves as an easily accessible supplement to doorstop-sized psychology textbooks Provides psychology students with psychology-specific statistics instruction Includes clear explanations and instruction on performing statistical analysis Teaches students how to analyze their data with SPSS, the most widely used statistical packages among students
Daniel Case suddenly has the opportunity to travel back in time, armed with all the knowledge he now possesses. Daniel is unhappy with his life. His home, his job, his trophy wife, all the trappings that go with his successful career as an insurance agent, it still leaves him feeling unfulfilled. So he jumps at the chance to grab something even better. Travelling to the past, Daniel is faced with some heavy choices. He could potentially make a real difference, stopping some or all of the atrocities that occurred since that time. He could use the power of his prescient knowledge to help stop poverty, world hunger, and disease. Or, he could disregard all of that and simply line his pockets. Daniel is on the most challenging journey of his life, a journey that is destined to change his very existence. The question is, for better or for worse? Time will tell. But it's not so much about where it all started as where it all ends. And that could change in a New York minute...for Daniel Case and everyone else in this and all possible alternative worlds.
This book is aimed at those studying and working in the field of health care, including nurses and the professions allied to medicine, who have little prior knowledge of statistics but for whom critical review of research is an essential skill. The book will provide support for those conducting literature-based projects which require the student to review evidence generated through empirical investigations. Evidence-based projects or assignments have, for several years formed the basis of a final year independent study for most honours degrees, and increasing numbers of masters programmes, in health care. Working from practical examples, exercises and illustrations, explanations will be given in (relatively) straightforward conceptual terms. This book is intended as a practical guide and reference book. Bullet points and illustrations will be used wherever possible, and dense text avoided. A detailed glossary of statistical concepts and terms will be provided as an additional resource for learning. The emphasis throughout will be to enable the student to transfer their learning to the research reports they are reading. Using fundamental criteria and aided by a list of key questions, students will be able to make an informed judgement about the quality of the research findings. The examples used will be based closely on actual research data, but essential details will be changed. This approach is intended to avoid problems of copyright and overcome the ethical problem of challenging published research in a forum where there is no right of the authors to reply. As follow-up exercises, students will be directed to references where they can test out their learning on ‘real’ examples, guided by key questions.
Statistics Using Stata uses a highly accessible and lively writing style to seamlessly integrate the learning of the latest version of Stata (17) with an introduction to applied statistics using real data in the behavioral, social, and health sciences. The text is comprehensive in its content coverage and is suitable at undergraduate and graduate levels. It requires knowledge of basic algebra, but no prior coding experience. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes a .do-file for each chapter, that was used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important take-aways of each chapter.
First published in 1986. Routledge is an imprint of Taylor & Francis, an informa company.
Biosocial criminology is an emerging perspective that highlights the interdependence between genetic and environmental factors in the etiology of antisocial behaviors. However, given that biosocial criminology has only recently gained traction among criminologists, there has not been any attempt to compile some of the "classic" articles on this topic. Beaver and Walsh's edited volume addresses this gap in the literature by identifying some of the most influential biosocial criminological articles and including them in a single resource. The articles covered in this volume examine the connection between genetics and crime, evolutionary psychology and crime, and neuroscience and crime. This volume will be a valuable resource for anyone interested in understanding the causes of crime from a biosocial criminological perspective.
Statistics is a subject that benefits many other disciplines in its application and has contributed tremendously to the advancement of medicine. In recognition of the central role of statistics in the health fields, certification agencies have incorporated this science into their requirements for knowledge acquisition by their members. This recognition is also reflected in the board exams, particularly those taken for clinical board specialty certification tests. This book reinforces statistical principles for those who have taken a course in the subject during their years of education. It provides many examples and exercises to allow the reader to review the material discussed. Its concise presentation and the repetition of ideas throughout the text help solidify the reader’s learning and retention of knowledge of the various topics presented.
The aim of this book is to equip biostatisticians and other quantitative scientists with the necessary skills, knowledge, and habits to collaborate effectively with clinicians in the healthcare field. The book provides valuable insight on where to look for information and material on sample size and statistical techniques commonly used in clinical research, and on how best to communicate with clinicians. It also covers the best practices to adopt in terms of project, time, and data management; relationship with collaborators; etc.
The text comprehensively discusses the fundamental aspects of human–computer interaction, and applications of artificial intelligence in diverse areas including disaster management, smart infrastructures, and healthcare. It employs a solution-based approach in which recent methods and algorithms are used for identifying solutions to real-life problems. This book: Discusses the application of artificial intelligence in the areas of user interface development, computing power analysis, and data management Uses recent methods/algorithms to present solution-based approaches to real-life problems in different sectors Showcases the applications of artificial intelligence and automation techniques to respond to disaster situations Covers important topics such as smart intelligence learning, interactive multimedia systems, and modern communication systems Highlights the importance of artificial intelligence for smart industrial automation and systems intelligence The book elaborates on the application of artificial intelligence in user interface development, computing power analysis, and data management. It explores the use of human–computer interaction for intelligence signal and image processing techniques. The text covers important concepts such as modern communication systems, smart industrial automation, interactive multimedia systems, and machine learning interface for the internet of things. It will serve as an ideal text for senior undergraduates, and graduate students in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
The contributions in this volume represent the latest research results in the field of Classification, Clustering, and Data Analysis. Besides the theoretical analysis, papers focus on various application fields as Archaeology, Astronomy, Bio-Sciences, Business, Electronic Data and Web, Finance and Insurance, Library Science and Linguistics, Marketing, Music Science, and Quality Assurance.