By using a simple pack of playing cards, the author of this book explains the important concepts of statistics covering many of the topics included in introductory statistics courses. He demonstrates: populations and variables; parameters; percentages; probability and sampling; sampling distribution; estimation; hypothesis testing; and two-by-two tables. Each chapter ends with a series of exercises to help the student manipulate the concept under discussion. Answers are included at the back of the text.

This co-edited book provides doctoral candidates with a practical, cross-discipline handbook for successfully navigating the doctoral process – from initial program selection to the final dissertation defense and preparing for the faculty interview. Invited chapters from established higher education experts cover topics ranging from university and program selection, preparing for comprehensive exams and dissertation research, self-care and self-management strategies, and recommendations for maintaining personal and professional support systems. Each chapter includes strategies for success and practical tips, including how to create a study guide for the comprehensive examination, how to create a professional support group, how to talk to your family about the doctoral process, how to select and work with a chair and committee, how to identify an appropriate research design, how to navigate the IRB process, and how to master the research and writing process.

The third edition of this popular, innovative and engaging textbook introduces students to the various methods of modern social science, explaining how these have emerged, their strengths and limitations for understanding the world in which we live, and how it is possible to combine methodological pluralism with intellectual rigour. Focussing on the debate between positivist and constructivist approaches, this new edition features contemporary research examples, expanded discussion of experimental methods, and a new emphasis on methods that have recently grown in popularity, such as process tracing and controlled randomized trials. This is the perfect textbook for students studying the philosophy of science in the context of political science or the social sciences more broadly, and it is essential reading for all those seeking to understand how different ways of knowing affect the methods we choose to study social phenomena. New to this Edition: - Contemporary research examples - A new emphasis on methods that have recently grown in popularity, such as random controlled trials, field experiments, big data and within-case and process tracing studies

You may stop looking now. Quantitative Nursing Research is the answer to the prayers of graduate students and practitioners who have sought the key to this often intimidating subject. In this highly readable (dare we say enjoyable?) work, Thomas R. Knapp guides the reader through the basic definitions, fundamentals of design, and techniques of quantitative research

Teaching Statistics Using Baseball is a collection of case studies and exercises applying statistical and probabilistic thinking to the game of baseball. Baseball is the most statistical of all sports since players are identified and evaluated by their corresponding hitting and pitching statistics. There is an active effort by people in the baseball community to learn more about baseball performance and strategy by the use of statistics. This book illustrates basic methods of data analysis and probability models by means of baseball statistics collected on players and teams. Students often have difficulty learning statistics ideas since they are explained using examples that are foreign to the students. The idea of the book is to describe statistical thinking in a context (that is, baseball) that will be familiar and interesting to students. The book is organized using a same structure as most introductory statistics texts. There are chapters on the analysis on a single batch of data, followed with chapters on comparing batches of data and relationships. There are chapters on probability models and on statistical inference. The book can be used as the framework for a one-semester introductory statistics class focused on baseball or sports. This type of class has been taught at Bowling Green State University. It may be very suitable for a statistics class for students with sports-related majors, such as sports management or sports medicine. Alternately, the book can be used as a resource for instructors who wish to infuse their present course in probability or statistics with applications from baseball. The second edition of Teaching Statistics follows the same structure as the first edition, where the case studies and exercises have been replaced by modern players and teams, and the new types of baseball data from the PitchFX system and fangraphs.com are incorporated into the text.

`This is a practical guide to carrying out research in counselling and the helping professions generally. It covers all major aspects of research and guides the reader through the essential processes involved, from setting up and conducting a study, to analyzing data and evaluating findings′ - New Therapist This practical, informative and encouraging guide to doing research in counselling and the helping professions generally has been written with practitioners firmly in mind. The book is a comprehensive yet accessible introduction which covers all major aspects of research and guides the reader through the essential processes involved, from setting up and conducting a study, to analyzing data and evaluating findings. In addition, the author provides guidelines for accessing research information and resources. With an emphasis on the acquisition of research skills and their practical application to counselling issues, Practitioner Research in Counselling shows how research can be used in a meaningful way by all practitioners.

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com