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To prepare for this Discussion, review the Lumley et al. (2002) (Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002). The importance of the normality assumption in large public health data sets, Annual Review of Public Health, 23(1), 151–170. doi:10.1146.annurev.publheath.23.100901.140546) article, as well as Lessons 19–21 and 24 in the Green and Salkind (2017) text. Use the Walden Library databases to identify a research example using your doctoral research proposal and consider the role and importance of the assumptions underlying each parametric test. My doctoral research proposal is about managing innovation and technology. Post a comparison of one-sample, paired-samples, and independent-samples t-tests within the context of quantitative doctoral business research. In your comparison, do the following:
Describe the research example related to your doctoral research proposal.
Describe a hypothetical example appropriate for each t-test, ensuring that the variables are appropriately identified.
Analyze the assumptions associated with the independent-samples t-tests and the implications when assumptions are violated.
Explain options researchers have when assumptions are violated.
