Replication in an experiment refers to the repetition of an experiment or observation in the same or similar conditions. It is an important aspect of experimental design as it adds information about the reliability of the conclusions or estimates to be drawn from the data. Here are some key points about replication in experiments:
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Replication can help to increase the reliability of experimental results by reducing the impact of random variation and errors.
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Replication can also help to identify systematic errors or biases in an experiment.
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In experimental design, replication can refer to assigning each treatment to many participants or repeating the entire experiment on a large group of subjects.
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Replicability is a related concept that refers to the ability to reproduce the results of an experiment or study. Replicability is an important issue in scientific research, as it ensures that findings are reliable and can be used to inform future research and decision-making.
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Replication can also be used to estimate the imprecision or random error of an analytical method.
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Replicates are multiple experimental runs with the same factor settings (levels) . Replicates are subject to the same sources of variability, independently of each other.
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Repeat measurements are taken during the same experimental run or consecutive runs, while replicate measurements are taken during identical but different experimental runs, which are often randomized.
In summary, replication in an experiment involves repeating an experiment or observation in the same or similar conditions to increase the reliability of the results and identify errors or biases. Replicability is the ability to reproduce the results of an experiment or study.
