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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.
Considerations about reproducibility can be placed into two categories. Reproducibility in the narrow sense refers to re-examining and validating the analysis of a given set of data. Replication refers to repeating the experiment or study to obtain new, independent data with the goal of reaching the same or similar conclusions.
The Reproducibility Project is a series of crowdsourced collaborations aiming to reproduce published scientific studies, finding high rates of results which could not be replicated. It has resulted in two major initiatives focusing on the fields of psychology [ 1 ] and cancer biology. [ 2 ]
In engineering, science, and statistics, replication is the process of repeating a study or experiment under the same or similar conditions to support the original claim, which is crucial to confirm the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]
The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results. [3] [4] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method.
Research transparency is a major aspect of scientific research. It covers a variety of scientific principles and practices: reproducibility, data and code sharing, citation standards or verifiability.
10 healthiest Thanksgiving side dishes. 1. Roasted Brussels sprouts. 2. Butternut squash soup. 3. Awesome sausage, apple, and cranberry stuffing. 4. Simple roasted butternut squash
An attribute agreement analysis is designed to simultaneously evaluate the impact of repeatability and reproducibility on accuracy. It allows the analyst to examine the responses from multiple reviewers as they look at several scenarios multiple times.