Cautionary Tales In Designed Experiments
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| Author | : David S. Salsburg |
| Publisher | : |
| Total Pages | : 94 |
| Release | : 2020-09-28 |
| Genre | : |
| ISBN | : 9781952363245 |
The beauty of DOE is about learning--from mistakes, from trying new things, and from working with others. Cautionary Tales in Designed Experiments aims to explain statistical design of experiments (DOE), Ronald Fisher's great innovation, to readers with minimal mathematical knowledge and skills. The book starts with historical examples and goes on to cover missteps, mismanaged experiments, learnings, the importance of randomization, and more. In later chapters, the book covers more statistical concepts, such as various designs for experiments, analysis of variance, Bayes' theorem in DOE, measurement, and when experiments fail. The book concludes by citing the ubiquity of statistical design of experiments.
| Author | : R. A. Bailey |
| Publisher | : Cambridge University Press |
| Total Pages | : 345 |
| Release | : 2008-04-17 |
| Genre | : Mathematics |
| ISBN | : 1139469916 |
This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. It does not choose from a menu of named designs. This approach requires a notation for units that does not depend on the treatments applied. Most structure on the set of observational units, or on the set of treatments, can be defined by factors. This book develops a coherent framework for thinking about factors and their relationships, including the use of Hasse diagrams. These are used to elucidate structure, calculate degrees of freedom and allocate treatment subspaces to appropriate strata. Based on a one-term course the author has taught since 1989, the book is ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.
| Author | : Stanley E. Lazic |
| Publisher | : Cambridge University Press |
| Total Pages | : 429 |
| Release | : 2016-12-08 |
| Genre | : Family & Relationships |
| ISBN | : 1107074290 |
A guide to designing lab-based biological experiments that have low bias, high precision and widely applicable results.
| Author | : Hans-Michael Kaltenbach |
| Publisher | : Springer Nature |
| Total Pages | : 281 |
| Release | : 2021-04-15 |
| Genre | : Mathematics |
| ISBN | : 3030696413 |
This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.
| Author | : Jeffrey R. Ferguson |
| Publisher | : University Press of Colorado |
| Total Pages | : 281 |
| Release | : 2010-05-15 |
| Genre | : Social Science |
| ISBN | : 1607320231 |
Designing Experimental Research in Archaeology is a guide for the design of archaeological experiments for both students and scholars. Experimental archaeology provides a unique opportunity to corroborate conclusions with multiple trials of repeatable experiments and can provide data otherwise unavailable to archaeologists without damaging sites, remains, or artifacts. Each chapter addresses a particular classification of material culture-ceramics, stone tools, perishable materials, composite hunting technology, butchering practices and bone tools, and experimental zooarchaeology-detailing issues that must be considered in the development of experimental archaeology projects and discussing potential pitfalls. The experiments follow coherent and consistent research designs and procedures and are placed in a theoretical context, and contributors outline methods that will serve as a guide in future experiments. This degree of standardization is uncommon in traditional archaeological research but is essential to experimental archaeology. The field has long been in need of a guide that focuses on methodology and design. This book fills that need not only for undergraduate and graduate students but for any archaeologist looking to begin an experimental research project.
| Author | : Mary Harrington |
| Publisher | : Cambridge University Press |
| Total Pages | : 201 |
| Release | : 2020-02-06 |
| Genre | : Medical |
| ISBN | : 1108492622 |
A student guide to neuroscience research including how to select a topic, analyze data, and present research.
| Author | : Renita Coleman |
| Publisher | : SAGE Publications |
| Total Pages | : 441 |
| Release | : 2018-08-27 |
| Genre | : Social Science |
| ISBN | : 1506377319 |
"This book is a must for learning about the experimental design–from forming a research question to interpreting the results this text covers it all." –Sarah El Sayed, University of Texas at Arlington Designing Experiments for the Social Sciences: How to Plan, Create, and Execute Research Using Experiments is a practical, applied text for courses in experimental design. The text assumes that students have just a basic knowledge of the scientific method, and no statistics background is required. With its focus on how to effectively design experiments, rather than how to analyze them, the book concentrates on the stage where researchers are making decisions about procedural aspects of the experiment before interventions and treatments are given. Renita Coleman walks readers step-by-step on how to plan and execute experiments from the beginning by discussing choosing and collecting a sample, creating the stimuli and questionnaire, doing a manipulation check or pre-test, analyzing the data, and understanding and interpreting the results. Guidelines for deciding which elements are best used in the creation of a particular kind of experiment are also given. This title offers rich pedagogy, ethical considerations, and examples pertinent to all social science disciplines.
| Author | : Michael Luca |
| Publisher | : MIT Press |
| Total Pages | : 229 |
| Release | : 2021-03-02 |
| Genre | : Business & Economics |
| ISBN | : 0262542277 |
How tech companies like Google, Airbnb, StubHub, and Facebook learn from experiments in our data-driven world—an excellent primer on experimental and behavioral economics Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of different online experiences. Once an esoteric tool for academic research, the randomized controlled trial has gone mainstream. No tech company worth its salt (or its share price) would dare make major changes to its platform without first running experiments to understand how they would influence user behavior. In this book, Michael Luca and Max Bazerman explain the importance of experiments for decision making in a data-driven world. Luca and Bazerman describe the central role experiments play in the tech sector, drawing lessons and best practices from the experiences of such companies as StubHub, Alibaba, and Uber. Successful experiments can save companies money—eBay, for example, discovered how to cut $50 million from its yearly advertising budget—or bring to light something previously ignored, as when Airbnb was forced to confront rampant discrimination by its hosts. Moving beyond tech, Luca and Bazerman consider experimenting for the social good—different ways that governments are using experiments to influence or “nudge” behavior ranging from voter apathy to school absenteeism. Experiments, they argue, are part of any leader's toolkit. With this book, readers can become part of “the experimental revolution.”
| Author | : James Evans |
| Publisher | : Routledge |
| Total Pages | : 319 |
| Release | : 2016-05-20 |
| Genre | : Science |
| ISBN | : 1317517148 |
This book explores how the concept or urban experimentation is being used to reshape practices of knowledge production in urban debates about resilience, climate change governance, and socio-technical transitions. With contributions from leading scholars, and case studies from the Global North and South, from small to large scale cities, this book suggests that urban experiments offer novel modes of engagement, governance, and politics that both challenge and complement conventional strategies. The book is organized around three cross-cutting themes. Part I explores the logics of urban experimentation, different approaches, and how and why they are deployed. Part II considers how experiments are being staged within cities, by whom, and with what effects? Part III examines how entire cities or groups of cities are constructed as experiments. This book seeks to contribute a deeper and more socially and politically nuanced understanding of how urban experiments shape cities and drive wider changes in society, providing a framework to examine the phenomenon of urban experimentation in conceptual and empirical detail.
| Author | : Peter Goos |
| Publisher | : John Wiley & Sons |
| Total Pages | : 249 |
| Release | : 2011-06-28 |
| Genre | : Science |
| ISBN | : 1119976162 |
"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.
