Some see triangulation as a method for corroborating findings and as a test for validity.
This assumes that a weakness in one method will be compensated for by another method, and that it is always possible to make sense between different accounts.
Bayesian hypothesis testing can minimize the risk in model selection by properly choosing the model acceptance threshold, and its results can be used in model averaging to avoid Type I /II errors.
Bayesian hypothesis testing can minimize the risk in model selection by properly choosing the model acceptance threshold, and its results can be used in model averaging to avoid Type I/II errors.
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 p-value metric in classical hypothesis testing.
Qualitative questions are open-ended such as ‘why do participants enjoy the program?
’ and ‘How does the program help increase self esteem for participants?
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.They use a systematic standardised approach and employ methods such as surveysand ask questions such as ‘what activities did the program run?Math Works Machine Translation The automated translation of this page is provided by a general purpose third party translator tool.50, Springer Heidelberg, Germany, from the same authors).A stricter method to test the association between the new-test-data (the x-data) and the control-test-data (y-values) is required.First, from the equation y = a bx it is tested whether the b-value is significantly different from 1,000, and the a-value is significantly different from 0,000.