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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.
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.
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.
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.
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.
How to Design and Report Experiments is the perfect textbook and guide to the often bewildering world of experimental design and statistics. It provides a complete map of the entire process beginning with how to get ideas about research, how to refine your research question and the actual design of the experiment, leading on to statistical procedure and assistance with writing up of results. While many books look at the fundamentals of doing successful experiments and include good coverage of statistical techniques, this book very importantly considers the process in chronological order with specific attention given to effective design in the context of likely methods needed and expected results. Without full assessment of these aspects, the experience and results may not end up being as positive as one might have hoped. Ample coverage is then also provided of statistical data analysis, a hazardous journey in itself, and the reporting of findings, with numerous examples and helpful tips of common downfalls throughout. Combining light humour, empathy with solid practical guidance to ensure a positive experience overall, How to Design and Report Experiments will be essential reading for students in psychology and those in cognate disciplines with an experimental focus or content in research methods courses.
Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to studies in psychology, education, life sciences, social sciences, medicine, and occupational and management research. The text covers: repeated measures unbalanced and non-randomized experiments and surveys choice of design adjustment for confounding variables model building and partition of variance covariance multiple regression Experiment Design and Statistical Methods contains a unique extension of the Venn diagram for understanding non-orthogonal design, and it includes exercises for developing the reader's confidence and competence. The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.
"Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover
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.