The direction of the test is indicated by the alternate Hypotheses H1. < indicates a left tailed test and > indicates a right tailed test. One would choose a two tailed test when the direction of < or > does not matter to the researcher. Two tailed tests are indicated by =. One would also choose a two tailed test if the rejection of the two tailed test guarantees a rejection of the left or right …show more content…
3 - Explain the difference between a left-tailed, two-tailed, and right-tailed test. When would you choose a two-tailed test? How might you tell the direction of the test by looking at a pair of hypotheses? How might you tell which direction (or no direction) to make the hypothesis by looking at the problem statement (research question)?
2 - Why does the significance level differ among industries? Is the null hypothesis more likely to be rejected at α = 0.01 than α = 0.10? As the significance level increases to α = 0.10 from α = 0.01, which type error is more likely to occur? What may be done to reduce the likelihood of incurring this error?
1 - What are the steps espoused by Applied Statistics in Business and Economics (or the instructor) for formal hypothesis testing? Explain why the sequence is important. What might happen if the hypothesis test is performed before the researcher has decided on the significance level?
Why is statistical significance not necessarily of practical important difference to a business decision? Provide an example and explain. Why do statisticians play only a limited role in deciding whether statistical significance requires a business action?
Statistical significance is not necessarily important because