How to Design and Report Experiments
How to Design and Report Experiments

Author: Andy Field

Publisher: SAGE

Published: 2002-12-20

Total Pages: 402

ISBN-13: 144626002X

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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.

Reproducibility and Replicability in Science
Reproducibility and Replicability in Science

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2019-10-20

Total Pages: 257

ISBN-13: 0309486165

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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.

Experimental and Quasi-Experimental Designs for Research
Experimental and Quasi-Experimental Designs for Research

Author: Donald T. Campbell

Publisher: Ravenio Books

Published: 2015-09-03

Total Pages: 172

ISBN-13:

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We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.