They use a systematic standardised approach and employ methods such as surveysand ask questions such as ‘what activities did the program run?
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Erzberger and Udo have used the term to refer to agreement between inferences.
Additionally the findings cannot be generalised to participants outside of the program and are only indicative of the group involved.
Quantitative approaches have the advantage that they are cheaper to implement, are standardised so comparisons can be easily made and the size of the effect can usually be measured.
Rather than seeing triangulation as a method for validation or verification, qualitative researchers generally use this technique to ensure that an account is rich, robust, comprehensive and well-developed.
Qualitative approaches aim to address the ‘how’ and ‘why’ of a program and tend to use unstructured methods of data collection to fully explore the topic.
Quantitative approaches however are limited in their capacity for the investigation and explanation of similarities and unexpected differences.’ and ‘what skills do staff need to implement the program effectively?
’ Both methods have their strengths and weaknesses.
It is also found that under some specific conditions, the Bayes factor metric in Bayesian equality hypothesis testing and the reliability-based metric can both be mathematically related to the -value metric in classical hypothesis testing.
Numerical studies are conducted to apply the above validation methods to gas damping prediction for radio frequency (RF) micro-electro-mechanical-system (MEMS) switches.
Formulations and implementation details are outlined for both equality and interval hypotheses.
Two types of validation experiments are considered—fully characterized (all the model/experimental inputs are measured and reported as point values) and partially characterized (some of the model/experimental inputs are not measured or are reported as intervals).
Qualitative approaches are good for further exploring the effects and unintended consequences of a program.