Final answer:
The ATU measures the impact of a treatment on those who were untreated. In medical studies, it helps in understanding what the potential outcomes could have been if the untreated had been treated. Descriptive statistics summarize the data, and inferential statistics are needed to draw conclusions.
Step-by-step explanation:
The "Average Treatment Effect for Untreated Group (ATU)" measures the difference in the expected outcome of individuals who have not received the treatment compared to what their outcomes would have been if they had received the treatment. It estimates the impact of the treatment on those who remained untreated. Understanding the ATU is crucial in medical studies to gauge the potential effectiveness of a treatment if it were to be extended to those not receiving it.
In the context of the examples given, if a scientist finds the average decrease in tumor size is larger for the drug-treated group compared to the untreated group, they cannot assume that the drug shrinks tumors without further analysis. They would need to conduct statistical hypothesis testing to determine if the differences are statistically significant and not due to random variation or other confounding factors.
When a scientist determines the average decrease in tumor size for the drug-treated group, this is considered descriptive statistics because it summarizes the data from that group. However, to make any inferential conclusions from this descriptive statistic, further inferential statistical procedures must be carried out.