Experimental Design and Statistics for Psychology: A First Course is a concise and accessible introduction to the design of psychology experiments and the statistical tests used to make sense of their results. Written in a straightforward, effective style and making abundant use of charts, diagrams and figures, this book assumes no prior knowledge of statistics and will be of benefit to all students needing a clear pathway into this often confusing area. The book introduces the main aspects of experimental design and statistics, including: how to formulate precise hypotheses and design experiments aimed at testing them. coverage of different aspects of experimental design. descriptive and inferential statistical analysis of experimental data. the difference between experimental and correlational studies. detailed instructions on how to perform statistical tests with SPSS. An invaluable step-by-step guide to all psychology students needing a firm grasp of the basics, Experimental Design and Statistics for Psychology: A First Course will also fire the imagination of more ambitious students by tackling some of the topic’s more complex, controversial issues. This book is also supported by an online password protected lecturer resource site which features test questions, downloadable figures and tables, and sample SPSS data-sets. Visit www.blackwellpublishing.com/sani.

For this second edition, this best-selling textbook has been revised, the coverage of two-sample tests extended, and new sections added introducing one-sample tests, linear regression, and the product-moment correlation coefficient.

This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.

A complete course in data collection and analysis for students who need to go beyond the basics. A true course companion, the engaging writing style takes readers through challenging topics, blending examples and exercises with careful explanations and custom-drawn figures ensuring the most daunting concepts can be fully understood.

This is the first textbook for psychologists which combines the model comparison method in statistics with a hands-on guide to computer-based analysis and clear explanations of the links between models, hypotheses and experimental designs. Statistics is often seen as a set of cookbook recipes which must be learned by heart. Model comparison, by contrast, provides a mental roadmap that not only gives a deeper level of understanding, but can be used as a general procedure to tackle those problems which can be solved using orthodox statistical methods.Statistics and Experimental Design for Psychologists focusses on the role of Occam's principle, and explains significance testing as a means by which the null and experimental hypotheses are compared using the twin criteria of parsimony and accuracy. This approach is backed up with a strong visual element, including for the first time a clear illustration of what the F-ratio actually does, and why it is so ubiquitous in statistical testing.The book covers the main statistical methods up to multifactorial and repeated measures, ANOVA and the basic experimental designs associated with them. The associated online supplementary material extends this coverage to multiple regression, exploratory factor analysis, power calculations and other more advanced topics, and provides screencasts demonstrating the use of programs on a standard statistical package, SPSS.Of particular value to third year undergraduate as well as graduate students, this book will also have a broad appeal to anyone wanting a deeper understanding of the scientific method.

This text is about doing science and the active process of reading, learning, thinking, generating ideas, designing experiments, and the logistics surrounding each step of the research process. In easy-to-read, conversational language, Kim MacLin teaches students experimental design principles and techniques using a tutorial approach in which students read, critique, and analyze over 75 actual experiments from every major area of psychology. She provides them with real-world information about how science in psychology is conducted and how they can participate. Recognizing that students come to an experimental design course with their own interests and perspectives, MacLin covers many subdisciplines of psychology throughout the text, including IO psychology, child psychology, social psychology, behavioral psychology, cognitive psychology, clinical psychology, health psychology, educational/school psychology, legal psychology, and personality psychology, among others. Part I of the text is content oriented and provides an overview of the principles of experimental design. Part II contains annotated research articles for students to read and analyze. New sections on how to critically evaluate media reports of scientific findings (in other words, how to identify ‘fake news’), authorship guidelines and decisions, survey research methods and AI tools have been included. Further, expanded information on the Open Science movement, and on ethics in research, and methods to achieve clarity and precision in thinking and writing are included. This edition is up to date with the latest APA Publication Manual (7th edition) and includes an overview of the bias-free language guidelines, the use of singular "they," and an ethical compliance checklist.. This text is essential reading for students and researchers interested in and studying experimental design in psychology.

This book presents an historical overview of the field--from its development to the present--at an accessible mathematical level. This edition features two new chapters--one on factor analysis and the other on the rise of ANOVA usage in psychological research. Written for psychology, as well as other social science students, this book introduces the major personalities and their roles in the development of the field. It provides insight into the disciplines of statistics and experimental design through the examination of the character of its founders and the nature of their views, which were sometimes personal and ideological, rather than objective and scientific. It motivates further study by illustrating the human component of this field, adding dimension to an area that is typically very technical. Intended for advanced undergraduate and/or graduate students in psychology and other social sciences, this book will also be of interest to instructors and/or researchers interested in the origins of this omnipresent discipline.

This book focuses on experimental research in two disciplines that have a lot of common ground in terms of theory, experimental designs used, and methods for the analysis of experimental research data: education and psychology. Although the methods covered in this book are also frequently used in many other disciplines, including sociology and medicine, the examples in this book come from contemporary research topics in education and psychology. Various statistical packages, commercial and zero-cost Open Source ones, are used. The goal of this book is neither to cover all possible statistical methods out there nor to focus on a particular statistical software package. There are many excellent statistics textbooks on the market that present both basic and advanced concepts at an introductory level and/or provide a very detailed overview of options in a particular statistical software programme. This is not yet another book in that genre. Core theme of this book is a heuristic called the question-design-analysis bridge: there is a bridge connecting research questions and hypotheses, experimental design and sampling procedures, and common statistical methods in that context. Each statistical method is discussed in a concrete context of a set of research question with directed (one-sided) or undirected (two-sided) hypotheses and an experimental setup in line with these questions and hypotheses. Therefore, the titles of the chapters in this book do not include any names of statistical methods such as ‘analysis of variance’ or ‘analysis of covariance’. In a total of seventeen chapters, this book covers a wide range of topics of research questions that call for experimental designs and statistical methods, fairly basic or more advanced.

Understanding and applying research methods and statistics in psychology is one of the corner stones of study at undergraduate level. To enable all undergraduate psychology students to carry out their own investigations the textbook covers basic and advanced qualitative and quantitative methods and follows a sequential structure starting from first principles to more advanced techniques. Accompanied by a companion website, the textbook: - Grounds all techniques to psychological theory relating each topic under discussion to well established pieces of research - Can be used by the student at beginning and more advanced undergraduate level - therefore a `one-stop′ shop - Includes a creative and practical selection of heuristic devices that cement knowledge of the techniques and skills covered in the textbook

"Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover