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Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
Example of direct replication and conceptual replication. There are two main types of replication in statistics. First, there is a type called “exact replication” (also called "direct replication"), which involves repeating the study as closely as possible to the original to see whether the original results can be precisely reproduced. [3]
The study also found that most Germans have positive perceptions of replication efforts: only 18% think that non-replicability shows that science cannot be trusted, while 65% think that replication research shows that science applies quality control, and 80% agree that errors and corrections are part of science.
Brian Nosek of University of Virginia and colleagues sought out to replicate 100 different studies, all published in 2008. [5] The project pulled these studies from three different journals, Psychological Science, the Journal of Personality and Social Psychology, and the Journal of Experimental Psychology: Learning, Memory, and Cognition, published in 2008 to see if they could get the same ...
In addition to the main result, Ioannidis lists six corollaries for factors that can influence the reliability of published research. Research findings in a scientific field are less likely to be true, the smaller the studies conducted. the smaller the effect sizes. the greater the number and the lesser the selection of tested relationships.
Replication (scientific method), one of the main principles of the scientific method, a.k.a. reproducibility Replication (statistics), the repetition of a test or complete experiment
AAPL Market Cap data by YCharts. Other noteworthy examples include selling out of oil and gas stocks during the downturn of 2020. In the last four years, the energy sector is up 129%.
The reproduction of past research has been a leading source of dissent. In an experimental setting, reproduction relies on the same set-up and apparatus, while replication only requires the use of the same methodology. Conversely, computational disciplines use reversed definitions of the term replicability and reproducibility. [1]