Daniël Lakens

This is the first comprehensive view of the work of scholars in several different disciplines contributing to the development of the psychology of science. This new field of inquiry is a systematic elaboration and application of psychological concepts and methods to clarify the nature of the scientific enterprise. While the psychology of science overlaps the philosophy, history, and sociology of science in important ways, its predominant focus is on individuals and small groups, rather than broad social institutions and concepts. The introduction surveys the field and traces its evolution in a historical context. Several contributors address epistemological issues raised by the psychology of science. Subsequent chapters discuss developments in the cognitive psychology of science, scientific theory, and the influence of social relationships on scientists' work. The conclusion proposes an agenda for further progress in this new approach to understanding science.

This accessibly written book reviews the controversy about significance testing, which has now crossed various disciplines as diverse as psychology, ecology, commerce, education, and biology, among others. It also introduces readers to alternative methods, especially effect size estimation (at both the group and case levels) and interval estimation (confidence intervals) in comparative studies. Basics of bootstrapping and Bayesian estimation are also considered. Research examples from substance abuse, education, learning, and other areas illustrate how to apply these methods. A companion website (www.apa.org/books/resources/kline) promotes learning by providing chapter exercises and sample answers, downloadable raw data files for many research examples, and links to other useful websites.

Hardcover: 370 pages Publisher: Free Pr; 2nd edition (February 1978) Language: English ISBN-10: 002907620X ISBN-13: 978-0029076200

Co-published with the University of Queensland Press. HPC holds rights in North America and U. S. Dependencies. Since its first publication in 1976, Alan Chalmers's highly regarded and widely read work--translated into eighteen languages--has become a classic introduction to the scientific method, known for its accessibility to beginners and its value as a resource for advanced students and scholars. In addition to overall improvements and updates inspired by Chalmers's experience as a teacher, comments from his readers, and recent developments in the field, this fourth edition features an extensive chapter-long postscript that draws on his research into the history of atomism to illustrate important themes in the philosophy of science. Identifying the qualitative difference between knowledge of atoms as it figures in contemporary science and metaphysical speculations about atoms common in philosophy since the time of Democritus offers a revealing and instructive way to address the question at the heart of this groundbreaking work: What is this thing called science?

Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Through this book's unique model comparison approach, students and researchers are introduced to a set of fundamental principles for analyzing data. After seeing how these principles can be applied in simple designs, students are shown how these same principles also apply in more complicated designs. Drs. Maxwell and Delaney believe that the model comparison approach better prepares students to understand the logic behind a general strategy of data analysis appropriate for various designs; and builds a stronger foundation, which allows for the introduction of more complex topics omitted from other books. Several learning tools further strengthen the reader's understanding: *flowcharts assist in choosing the most appropriate technique; *an equation cross-referencing system aids in locating the initial, detailed definition and numerous summary equation tables assist readers in understanding differences between different methods for analyzing their data; *examples based on actual research in a variety of behavioral sciences help students see the applications of the material; *numerous exercises help develop a deeper understanding of the subject. Detailed solutions are provided for some of the exercises and *realistic data sets allow the reader to see an analysis of data from each design in its entirety. Updated throughout, the second edition features: *significantly increased attention to measures of effects, including confidence intervals, strength of association, and effect size estimation for complex and simple designs; *an increased use of statistical packages and the graphical presentation of data; *new chapters (15 & 16) on multilevel models; *the current controversies regarding statistical reasoning, such as the latest debates on hypothesis testing (ch. 2); *a new preview of the experimental designs covered in the book (ch. 2); *a CD with SPSS and SAS data sets for many of the text exercises, as well as tutorials reviewing basic statistics and regression; and *a Web site containing examples of SPSS and SAS syntax for analyzing many of the text exercises. Appropriate for advanced courses on experimental design or analysis, applied statistics, or analysis of variance taught in departments of psychology, education, statistics, business, and other social sciences, the book is also ideal for practicing researchers in these disciplines. A prerequisite of undergraduate statistics is assumed. An Instructor's Solutions Manual is available to those who adopt the book for classroom use.

For thirty years, Peter Singer's Practical Ethics has been the classic introduction to applied ethics. For this third edition, the author has revised and updated all the chapters, and added a new chapter addressing climate change, one of the most important ethical challenges of our generation. Some of the questions discussed in this book concern our daily lives. Is it ethical to buy luxuries when others do not have enough to eat? Should we buy meat from intensively reared animals? Am I doing something wrong if my carbon footprint is above the global average? Other questions confront us as concerned citizens: equality and discrimination on the grounds of race or sex; abortion, the use of embryos for research, and euthanasia; political violence and terrorism; and the preservation of our planet's environment. This book's lucid style and provocative arguments make it an ideal text for university courses and for anyone willing to think about how she or he ought to live.

In this instant New York Times Bestseller, Geoff Smart and Randy Street provide a simple, practical, and effective solution to what The Economist calls “the single biggest problem in business today”: unsuccessful hiring. The average hiring mistake costs a company $1.5 million or more a year and countless wasted hours. This statistic becomes even more startling when you consider that the typical hiring success rate of managers is only 50 percent. The silver lining is that “who” problems are easily preventable. Based on more than 1,300 hours of interviews with more than 20 billionaires and 300 CEOs, Who presents Smart and Street’s A Method for Hiring. Refined through the largest research study of its kind ever undertaken, the A Method stresses fundamental elements that anyone can implement–and it has a 90 percent success rate. Whether you’re a member of a board of directors looking for a new CEO, the owner of a small business searching for the right people to make your company grow, or a parent in need of a new babysitter, it’s all about Who. Inside you’ll learn how to • avoid common “voodoo hiring” methods • define the outcomes you seek • generate a flow of A Players to your team–by implementing the #1 tactic used by successful businesspeople • ask the right interview questions to dramatically improve your ability to quickly distinguish an A Player from a B or C candidate • attract the person you want to hire, by emphasizing the points the candidate cares about most In business, you are who you hire. In Who, Geoff Smart and Randy Street offer simple, easy-to-follow steps that will put the right people in place for optimal success.

Analyses the work of science as the creation and investigation of problems, and demonstrates the role of choice and value-judgement, and the inevitability of error, in scientific research.

How can we objectively define categories of truth in scientific thinking? How can we reliably measure the results of research? In this ground-breaking text, Dienes undertakes a comprehensive historical analysis of the dominant schools of thought, key theories and influential thinkers that have progressed the foundational principles and characteristics that typify scientific research methodology today. This book delivers a masterfully simple, 'though not simplistic', introduction to the core arguments surrounding Popper, Kuhn and Lakatos, Fisher and Royall, Neyman and Pearson and Bayes. Subsequently, this book clarifies the prevalent misconceptions that surround such theoretical perspectives in psychology today, providing an especially accessible critique for student readers. This book launches an informative inquiry into the methods by which psychologists throughout history have arrived at the conclusions of research, equipping readers with the knowledge to accurately design and evaluate their own research and gain confidence in critiquing results in psychology research. Particular attention is given to understanding methods of measuring the falsifiability of statements, probabilities and the differing views on statistical inference. An illuminating book for any undergraduate psychology student taking courses in critical thinking, research methods, BPS's core area 'conceptual and historical issues' as well as those studying masters, phd's and experienced researchers.