Maria tests the effectiveness of an anti-depression drug by recruiting 500 participants and randomly assigning half e participan
ts to take Drug A for 1 month and the other half to take a placebo for 1 month. At the end of the month, depression levels are recorded. Overall, participants who received Drug A had depression scores of M-32.12, SD- 10.58 and those you received the placebo had depression scores of M- 34.29. SD 11.10, t(498) 2.17,p .01 (one tailed], d19. Faced with these data, Maria needs to write a report in which she interprets the data. Which of the following is the best summary of these data? A. The p value is very small, showing that there is only a 1% chance of a Type l error. we can be 99% confident that the drug significantly reduces depression.
B. The results of the t-test are significant, but the effect size is small. This study should be replicated with a larger sample size to increase statistical power.
C. The results of the t-test are significant, but the effect size is small. The drug does lower depression, but it is not clear if the reduction is enough to warrant use of the drug.
D. The small p value and the small effect size suggest that the observed difference between the drug adplacebo groups are likely to be due to sampling error. This study should be replicated with a larger sample size.
D. The small p value and the small effect size suggest that the observed difference between the drug placebo groups are likely to be due to sampling error. This study should be replicated with a larger sample size.
Step-by-step explanation:
The p value is determined for any test before making a conclusion. If the p-value is smaller than critical value then we reject the null hypothesis which means that drug is not effective for the reducing depression. A very small p-value usually lesser than 0.05 indicates strong evidence against the null hypothesis.
