Google Trends Dissected:Old Statistical Methods, New Insights from a Quantitive research methodology prioritizing Probababilistic analysis

Results which help in postulating Public policy for future pandemics’ lockdowns: ● From the binomial distribution, I find that out of any random sample of internet users (belonging to the listed 27 high internet penetrated states), 25% to 50% of them will be optimistic (with 98.42% confidence, during lockdown period). ● I find significant evidence that average overall concern during the post-lockdown period is lower than during the lockdown period. ● I find no significant evidence that states with higher internet penetration are more optimistic than states with lower internet penetration. ● I find significant evidence that average pessimistic concern during the post-lockdown period is lower than during the lockdown period. ● I do not find significant evidence that average optimistic concern during the post-lockdown period is lower than during the lockdown period.可为未来大流行病封锁相关公共政策的制定提供参考的研究结果： ● 基于二项分布（binomial distribution），研究显示：在随机抽取的、隶属于27个高互联网普及率（internet penetration）州的互联网用户样本中，有25%至50%的用户在封锁期间持乐观态度，该结论的置信度达98.42%。 ● 存在显著证据表明，后封锁时期的整体平均担忧水平低于封锁期间。 ● 未发现显著证据表明互联网普及率更高的州相较于互联网普及率更低的州更为乐观。 ● 存在显著证据表明，后封锁时期的平均悲观担忧水平低于封锁期间。 ● 未发现显著证据表明后封锁时期的平均乐观担忧水平低于封锁期间。