Everything about Replication Statistics totally explained
In
engineering,
science, and
statistics,
replication is the repetition of an
experimental condition so that the variability associated with the phenomenon can be estimated.
ASTM, in
standard E1847, defines replication as "the repetition of the set of all the treatment combinations to be compared in an experiment. Each of the repetitions is called a replicate."
Replication isn't the same as repeated
measurements: they're dealt with differently in statistical
experimental design and
data analysis.
For proper
sampling, a process or batch of products should be in reasonable statistical control; inherent
random variation is present but variation do to assignable (special) causes is not. Evaluation or testing of a single item doesn't allow for item-to-item variation and may not represent the batch or process. Replication is needed to account for this variation among items and treatments.
Example
As an example, consider a continuous process which produces items. Batches of items are then processed or treated. Finally, tests or measurements are conducted. Several options might be available to obtain ten test values. Some possibilities are:
- One finished and treated item might be measured repeatedly to obtain ten test results. Only one item was measured so there's no replication. The repeated measurements help identify observational error.
- Ten finished and treated items might be taken from a batch and each measured once. This isn't full replication because the ten samples are not random and not representative of the continuous nor batch processing.
- Five items are taken from the continuous process based on sound statistical sampling. These are processed in a batch and tested twice each. This includes replication of initial samples but doesn't allow for batch-to-batch variation in processing. The repeated tests on each provide some measure and control of testing error.
- Five items are taken from the continuous process based on sound statistical sampling. These are processed in five different batches and tested twice each. This plan includes proper replication of initial samples and also includes batch-to-batch variation. The repeated tests on each provide some measure and control of testing error.
Each option would call for different
data analysis methods and yield different conclusions.
Further Information
Get more info on 'Replication Statistics'.
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