Your firm will base some expensive decisions on the results of your hypothesis test, so your boss wants to have a high standard
of evidence for rejecting the null hypothesis. What should you do? A. Throw out observations that look suspicious
B. Increase the significance level to 10%
C. Reduce the significance level to 1%
D. Keep the significance level the same but collect more data
D. Keep the significance level the same but collect more data
Step-by-step explanation:
The significance level is the probability of rejecting the null hypothesis when it is true. For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference. This significance level is usually established initially and does not need to be changed.
But, you can collect more data to gain a high standard of evidence for rejecting the null hypothesis. More data gives more evidence and leads to a result that is not attributed to chance, thus, proving that the result is statistically significant.
