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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]
For example, several agricultural field experiments have run for more than 100 years, but much shorter experiments may qualify as "long-term" in other disciplines. An experiment is "a set of actions and observations", implying that one or more treatments (fertilizer, subsidized school lunches, etc.) is imposed on the system under study.
Some fields use smaller p-values, such as p < 0.01 (1% chance of a false positive) or p < 0.001 (0.1% chance of a false positive). But a smaller chance of a false positive often requires greater sample sizes or a greater chance of a false negative (a correct hypothesis being erroneously found incorrect).
The two men behind the so-called “Doomsday vault” holding 1.25 million seed samples ― seeds that can be used to rebuild much the world's food supply if catastrophe hits ― are this year’s ...
The first part is the time (time_high and time_low combined). The reserved field is skipped. The family field comes directly after the first dot, so in this case 0d (13 in decimal) for DDS (Data Distribution Service). The remaining parts, each separated with a dot, are the node bytes.
In this example, all samples are performed in duplicate. The assay is a colorimetric assay in which a spectrophotometer can measure the amount of protein in samples by detecting a colored complex formed by the interaction of protein molecules and molecules of an added dye. In the illustration, the results for the diluted test samples can be ...
All analytical procedures should be validated. Identification tests are conducted to ensure the identity of an analyte in a sample through comparison of the sample to a reference standard through methods such as spectrum, chromatographic behavior, and chemical reactivity. [5] Impurity testing can either be a quantitative test or a limit test.
In computing, data deduplication is a technique for eliminating duplicate copies of repeating data. Successful implementation of the technique can improve storage utilization, which may in turn lower capital expenditure by reducing the overall amount of storage media required to meet storage capacity needs.