Experimental archaeology is today forging new links between archaeological scientists and theorists. Many of the best archaeological projects today are those which use methodology and interpretation from both the sciences and the arts. The papers presented here reflect this interdisciplinary approach and focus on sites and material culture spanning from the Mesolithic to the Late Medieval periods. They range from the history of experimentation in archaeology and its place within the field today, to the theory behind `the experiment', to several projects which have used controlled experimentation to test hypotheses about archaeological remains, past actions, and the scientific processes we use. Now that archaeology has moved beyond the focus of the Processual/Post-Processual debates of the 1970s and 80s, which pitted science against the arts, archaeologists have more freedom to choose how to `do archaeology'. The contributions to this book reflect this as problems are approached in --

A brief, authoritative introduction to field experimentation in the social sciences. Written by two leading experts on experimental methods, this concise text covers the major aspects of experiment design, analysis, and interpretation in clear language. Students learn how to design randomized experiments, analyze the data, and interpret the findings. Beyond the authoritative coverage of the basic methodology, the authors include numerous features to help students achieve a deeper understanding of field experimentation, including rich examples from the social science literature, problem sets and discussions, data sets, and further readings.

First published in 1996, this book is a logical and consistent approach to experimental design using statistical principles.

This 2001 book provides a practical and systematic approach to the acquisition, interpretation, and reporting of physiologic responses to exercise. Pulmonologists, cardiologists, and sports physicians, as well as respiratory therapists and other allied health professionals will find this book an indispensable resource when learning to select proper instruments, identify the most appropriate test protocols, and integrate and interpret physiologic response variables. The final chapter presents clinical cases to illuminate useful strategies for exercise testing and interpretation. Useful appendices offer laboratory forms, algorithms and calculations, as well as answers to FAQs. A glossary of terms, symbols, and definitions is also included. Exercise Testing and Interpretation: A Practical Approach offers clearly defined responses (both normal and abnormal) to over thirty performance variables including aerobic, cardiovascular, ventilatory, and gas-exchange variables. Practical, portable, and easy-to-read, this essential guidebook can be used as a complement to more detailed books on the topic, or stand on its own.

This volume focuses on the role and means of archaeological experimentation in understanding the processes involved in the manufacture and use of past artifacts. When asking for contributions, we suggested the five stages of an experimental approach as main-themes: 1. Selection and acquisition of raw material, identical to those present in the archaeological assemblages. 2. Production of replicas following the technological transformation schemes identified by the direct study of archaeological items. 3. Experimental use as indicated by the publications/ethnographic comparisons or as suggested by the morphology/use-wear evolution of the archaeological items. 4. Microscopical analysis of use-wear patterns. 5. Comparison of experimental data with archaeological data in order to validate the existing hypotheses on the way they were manufactured and used by the human communities. A second aim was that the invited authors to have various archaeological backgrounds and cover a broad spatial and temporal interval. As a result, this volume comprises 17 studies organized in three sections, dictated by the various aspects of experimental archaeology they represent: from the more traditional experimental replication, understanding and interpretation of artefact functionality, and relatively recent (and less trodden) directions in experimental archaeology. It also comes to show that experimental archaeology is as well suited for Palaeolithic studies, as it is for the Neo-Eneolithic and the Bronze Age. Although most papers refer geographically to Europe, interesting contributions take us to Argentina and Australia. *** Acest volum se concentrează pe rolul și mijloacele experimentelor arheologice în înțelegerea proceselor implicate în fabricarea și utilizarea artefactelor din trecut. Am invitat o serie de specialiștii să contribuie cu studii care să testeze ipotezele teoretice existente, dar și altele care să aducă abordări inovatoare. Când am solicitat contribuții, am sugerat ca teme principale cele cinci etape ale demersului experimental: 1. Selectarea și achiziționarea de materii prime, identice cu cele prezente în ansamblurile arheologice. 2. Realizarea de replici urmând schemele de transformare tehnologică identificate prin studiul direct al ansamblurilor arheologice. 3. Utilizarea experimentală după cum este indicată de publicații/comparații etnografice sau sugerată de evoluția uzurii pe artefactele arheologice. 4. Analiza microscopică a modelelor de de uzură. 5. Compararea datelor experimentale cu datele arheologice în vederea validării ipotezelor existente privind fabricarea și utilizarea lor de către comunitățile umane. Un al doilea scop al volumului a fost ca autorii invitați să provină din diferite medii arheologice și să acopere un interval spațial și temporal larg. A rezultat un volum cuprinzând 17 studii organizate în trei secțiuni, dictate de diversele aspecte ale arheologiei experimentale: replicarea experimentală la nivel tehnologic, înțelegerea și interpretarea funcționalității artefactelor și direcțiile relativ recente (interdisciplinare) în cadrul experimentului arheologie. De asemenea, volumul ne-a arătat că arheologia experimentală este la fel de potrivită pentru studiile paleolitice, ca și pentru neo-eneolitic și epoca bronzului. Deși majoritatea lucrărilor se referă geografic la Europa, contribuții interesante vin din Argentina sau Australia.

Clearly written and free of statistical jargon, this invaluableguide concentrates on the practicalities of statistical analysisfor anyone involved with agricultural research. Each section starts with the key points, giving a quick referenceto the contents and plenty of examples using 'real' data. Successful experiment design starts with a statement of aims. Theauthors guide the reader through planning an experiment, includingdefining objectives, considering treatments, measurements ofinterest and the time and timing of assessments. Advantages anddisadvantages of different experiment designs and the importance ofdata exploration and graphical presentation are covered, as aredata collection, storage, validation and verification. Statisticaltechniques include the t-test, anlaysis of variance, basicregression analysis and non-parametric techniques. Assumptionsinherent to these techniques are clearly identified (bearing inmind the principles and aims) without losing the reader instatistical theory. All of the techniques are illustrated withworked examples and give full interpretation of the results.Formulae are kept to a minimum in the main text, but are given infull in the appendix.

Russian physiologist and Nobel Prize winner Ivan Pavlov is most famous for his development of the concept of the conditioned reflex and the classic experiment in which he trained a dog to salivate at the sound of a bell. In this study, Daniel P. Todes explores Pavlov's early work in digestive physiology through the structures and practices of his landmark laboratory - the physiology department of the Imperial Institute for Experimental Medicine.

Like other sciences and engineering disciplines, software engineering requires a cycle of model building, experimentation, and learning. Experiments are valuable tools for all software engineers who are involved in evaluating and choosing between different methods, techniques, languages and tools. The purpose of Experimentation in Software Engineering is to introduce students, teachers, researchers, and practitioners to empirical studies in software engineering, using controlled experiments. The introduction to experimentation is provided through a process perspective, and the focus is on the steps that we have to go through to perform an experiment. The book is divided into three parts. The first part provides a background of theories and methods used in experimentation. Part II then devotes one chapter to each of the five experiment steps: scoping, planning, execution, analysis, and result presentation. Part III completes the presentation with two examples. Assignments and statistical material are provided in appendixes. Overall the book provides indispensable information regarding empirical studies in particular for experiments, but also for case studies, systematic literature reviews, and surveys. It is a revision of the authors’ book, which was published in 2000. In addition, substantial new material, e.g. concerning systematic literature reviews and case study research, is introduced. The book is self-contained and it is suitable as a course book in undergraduate or graduate studies where the need for empirical studies in software engineering is stressed. Exercises and assignments are included to combine the more theoretical material with practical aspects. Researchers will also benefit from the book, learning more about how to conduct empirical studies, and likewise practitioners may use it as a “cookbook” when evaluating new methods or techniques before implementing them in their organization.

The tools and techniques used in Design of Experiments (DoE) have been proven successful in meeting the challenge of continuous improvement in many manufacturing organisations over the last two decades. However research has shown that application of this powerful technique in many companies is limited due to a lack of statistical knowledge required for its effective implementation.Although many books have been written on this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as through using statistical methods and readers will find the concepts in this book both familiar and easy to understand.This new edition includes a chapter on the role of DoE within Six Sigma methodology and also shows through the use of simple case studies its importance in the service industry. It is essential reading for engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. - Written in non-statistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE - Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem solving methodology - New edition includes a full chapter on DoE for services as well as case studies illustrating its wider application in the service industry

One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.