Final Answer:
No my answers in a would not change if x₁ and or x₂ were not normally distributed. The assumptions of normality are not necessary for the validity of the answers provided in a.
Step-by-step explanation:
The answers in a are likely derived from statistical methods or analyses that do not strictly require the assumption of normality for x₁ and x₂. For instance if the question pertains to hypothesis testing or confidence intervals for means large sample sizes can lead to robust results even in the absence of normality. Additionally some statistical tests such as the Central Limit Theorem allow for valid inferences under departures from normality as long as the sample size is sufficiently large.
Moreover non-parametric methods which do not assume a specific distribution could be employed in situations where normality is not met. These methods like the Wilcoxon rank-sum test or the Mann-Whitney U test can be effective alternatives for comparing groups or assessing relationships.
In summary the validity of answers in a is contingent on the specific statistical methods employed and their underlying assumptions. If the methods used are robust to departures from normality the conclusions drawn in a would remain valid emphasizing the importance of selecting appropriate statistical techniques based on the characteristics of the data at hand.