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Discussion Prompt
Nishishiba et al. (2013) explain in chapter 9 that “T-tests ar
Discussion Prompt
Nishishiba et al. (2013) explain in chapter 9 that “T-tests are the statistical tests you can use when you have a research question that requires a comparison of two means. This requires a dependent variable that is a continuous measure.”
When comparing means, why is it important to perform a t-test rather than just looking at the differences in the means? How would you explain this to a policymaker? (see pages 174-175)
And now for the debate ..
One of the assumptions of the T-test is that “the variable from which the mean is calculated must be normally distributed. If there is a sample size of less than 15, then the … t-test is not an appropriate choice as outliers heavily influence the data” (Nishishiba et al., 2013, p.176).
So, let’s say you have a sample size of 15 employees each in two groups. Can you use a T-test to detect statistical difference in the mean job satisfaction level of the two groups? Or should you never, ever use a T-test with a sample size that is less than 40? Is there even a minimum sample size? Explain. (see assumptions of T-test pages, 176, 178, and 186).
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