Importance of Assumptions and Post-Hoc Tests
Too often, researchers rely heavily on whether a p value is less than .05 or whether an “r” is close to +/- 1. But both assumptions and post-hoc tests ensure that all factors have been adequately considered.
Develop an original response proposing a scenario where either: assumptions tests were not properly performed, and the wrong statistical procedure was applied, giving inaccurate results; or post-hoc procedures were not applied to contextualize the results and, although the null hypothesis was rejected, power and effect were not considered.
Describe the scenario hypothetically and propose ways you could avoid such situations in your own application of statistics in research in the future.
Why Are Assumptions and Post-Hoc Tests Needed?
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Why Are Assumptions and Post-Hoc Tests Needed?
Scenario
In a hypothetical research study examining the relationship between sleep duration and academic performance, the researchers failed to properly perform assumptions tests before applying a parametric statistical procedure. They assumed that the data met the assumptions of normality and homogeneity of variance, leading them to use a t-test to compare the mean academic performance scores between two groups with different sleep durations. However, upon closer inspection, the assumptions tests would have revealed that the academic performance scores were not normally distributed, and the variances between the groups were significantly different. Ignoring these violations of assumptions, the researchers proceeded with the t-test, leading to inaccurate results and potentially