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This estimate can then be compared to the findings of observational research. Note that benchmarking is an attempt to calibrate non-statistical uncertainty (flaws in underlying assumptions). When combined with meta-analysis this method can be used to understand the scope of bias associated with a specific area of research.
The term benchmark, originates from the history of guns and ammunition, in regards to the same aim as for the business term: comparison and improved performance. The introduction of gunpowder arms replaced the bow and arrow from the archer, who now had to learn to handle a gun.
Benchmark (surveying), a point of known elevation marked for the purpose of surveying; Benchmarking (geolocating), an activity involving finding benchmarks; Benchmark (computing), the result of running a computer program to assess performance; Benchmark, a best-performing, or gold standard test in medicine and statistics
A non-optimal design requires a greater number of experimental runs to estimate the parameters with the same precision as an optimal design. In practical terms, optimal experiments can reduce the costs of experimentation.
Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).
The data from a study can also be analyzed to consider secondary hypotheses inspired by the initial results, or to suggest new studies. A secondary analysis of the data from a planned study uses tools from data analysis, and the process of doing this is mathematical statistics. Data analysis is divided into:
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A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or irrelevant answers. [1] Incorporated in the design of a research study will depend on the standpoint of the researcher over their beliefs in the nature of knowledge (see epistemology) and reality (see ontology), often shaped by ...