@anchorage98
200+ people (who had been vaccinated and dies from Covid) is a not a very small sample. Singapore is the one of the only places who used all the 4 vaccines, and who have the most recent data. Nobody, in his right mind, can call this as cherry picking.
200 多人（接种过疫苗并死于 Covid）并不是一个很小的样本。新加坡是唯一使用所有 4 种疫苗并拥有最新数据的地方之一。没有人，如果他头脑还可以称为清醒的话，可以称之为断章取义。
@standardpoodle
Yes, you raised a legitimate argument.
In this case, please tell us 1) What is the standard deviation (sample size is 200), 2) What is the standard error, 3) or what is chance that Sinovac or 国药疫苗 is of 50% or higher efficacy of Moderna.
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是的，你提出了一个合理的论点。
在这种情况下，请告诉我们 1) 标准差是多少（样本量为 200），2) 标准差是多少，3) 或者科兴生物, 国药疫苗 达到 Moderna 50% 或更高功效的几率是多少
先从简单的看起吧。。。我不收你的学费了。。。
https://home.csulb.edu/~msaintg/ppa696/696stsig.htm
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newbigman 发表评论于 2022-01-13 16:20:50
@standardpoodle
Yes, you raised a legitimate argument.
In this case, please tell us 1) What is the standard deviation (sample size is 200), 2) What is the standard error, 3) or what is chance that Sinovac or 国药疫苗 is of 50% or higher efficacy of Moderna.
===
是的，你提出了一个合理的论点。
在这种情况下，请告诉我们 1) 标准差是多少（样本量为 200），2) 标准差是多少，3) 或者科兴生物, 国药疫苗 达到 Moderna 50% 或更高功效的几率是多少
算我仁慈，怕没有给出全面网站的网址。。。
我增加点内容看看。。。。
What Are Tests for Significance
Two questions arise about any hypothesized relationship between two variables:
1) what is the probability that the relationship exists;
2) if it does, how strong is the relationship
There are two types of tools that are used to address these questions: the first is addressed by tests for statistical significance; and the second is addressed by Measures of Association.
Tests for statistical significance are used to address the question: what is the probability that what we think is a relationship between two variables is really just a chance occurrence?
If we selected many samples from the same population, would we still find the same relationship between these two variables in every sample? If we could do a census of the population, would we also find that this relationship exists in the population from which the sample was drawn? Or is our finding due only to random chance?
Tests for statistical significance tell us what the probability is that the relationship we think we have found is due only to random chance. They tell us what the probability is that we would be making an error if we assume that we have found that a relationship exists.
We can never be completely 100% certain that a relationship exists between two variables. There are too many sources of error to be controlled, for example, sampling error, researcher bias, problems with reliability and validity, simple mistakes, etc.
But using probability theory and the normal curve, we can estimate the probability of being wrong, if we assume that our finding a relationship is true. If the probability of being wrong is small, then we say that our observation of the relationship is a statistically significant finding.
Statistical significance means that there is a good chance that we are right in finding that a relationship exists between two variables. But statistical significance is not the same as practical significance. We can have a statistically significant finding, but the implications of that finding may have no practical application. The researcher must always examine both the statistical and the practical significance of any research finding.
For example, we may find that there is a statistically significant relationship between a citizen's age and satisfaction with city recreation services. It may be that older citizens are 5% less satisfied than younger citizens with city recreation services. But is 5% a large enough difference to be concerned about?
Often times, when differences are small but statistically significant, it is due to a very large sample size; in a sample of a smaller size, the differences would not be enough to be statistically significant.
Steps in Testing for Statistical Significance
1) State the Research Hypothesis
2) State the Null Hypothesis
3) Select a probability of error level (alpha level)
4) Select and compute the test for statistical significance
5) Interpret the results
1) State the Research Hypothesis
。。。。。。。。。。。。。。
https://home.csulb.edu/~msaintg/ppa696/696stsig.htm
医学差别显著性检验可真是现代生物医学研究基本的东西了。。。任何一个生物医学专业的都应该知晓的，要不您请问题哥代劳一下吧。。。
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newbigman 发表评论于 2022-01-13 16:56:45
Are you seriously wanting me to go through the tedious article, especially after long working day?
Since you're so knowledgeable about statistic, calculating the chance that Sinovac or 国药疫苗 is of 50% or higher efficacy of Moderna should not be a challenge for you right?
As said by Sir Francis Bacon, "knowledge is power", with that calculated #, you can defend your SinoVac or your 国药疫苗 more effectively. Did I motivate you enough?
我指出了你的问题，都把你该学的地方告诉你了。。。学不学，进步不进步，有没有造化就看你自己的。。。
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newbigman 发表评论于 2022-01-13 17:09:57
One guest shall not bother two hosts.
I think you are the best candidate to do it.
中国研发及生产的新冠疫苗 自由亚洲电台制图
全球病毒肆虐，各厂牌疫苗的效力也被广泛讨论。新加坡有数据显示，中国科兴疫苗的染疫死亡率较其它品牌高。不过根据科兴生物公司财报，去年上半年的净利润比前年同期暴增162倍。
新加坡最新公布的数据显示，中国研发的国药和科兴疫苗，在完全接种后的染疫死亡率上输给莫德纳和辉瑞疫苗，尤其接种科兴后的染疫死亡率最高。
马来西亚一名建筑工人2021年6月8日接种中国生产的科兴疫苗（路透社）
新加坡卫生部长王乙康1月10日在新加坡国会作证时透露，新加坡2021年共有802人因感染新冠病毒而身亡，其中555人没有完全接种疫苗。在有接种疫苗的死亡率上，接种中国科兴疫苗的最高，接下来是国药和辉瑞，莫德纳则是最低。不过王乙康也表示这些数据仅供参考，没有加入其他影响死亡率的因素，例如年龄和接种疫苗的时间。
中国国药和科兴两款都是较为传统的灭活病毒疫苗，由已杀灭的病原体製成，主要通过其中的抗原诱导细胞免疫的产生，而莫德纳和辉瑞疫苗则是使用信使核糖核酸（mRNA），抽取病毒内部分核糖核酸编码蛋白製成疫苗，注射后能使人体内细胞生成触发体内免疫应答的蛋白质。
灭活疫苗效果有限 加强剂施打种类很重要
针对不同疫苗的效力，台湾中研院生物医学科学研究所研究员何美乡告诉本台，灭活疫苗是传统疫苗的製备技术，使用广泛，而信使核糖核酸疫苗虽然是较新的技术，但也有十几年以上的研究历史，虽然尚未有完整科学实验确定信使核糖核酸疫苗百分之百胜出，但现行阶段是有这样的推论。
“在这样的原则下，当然mRNA疫苗我们预测会比较好。事实上是不是比较好？我们还不知道，因为还没有那麽多蛋白质疫苗跟它在真实世界比较，但应该是比较好，因为我们可以看到蛋白质疫苗被淘汰的很多。”何美乡说。
总部在韩国的国际疫苗研究所（International Vaccine Institute）总干事杰罗姆·金（Jerome Kim）曾表示，若只看灭活疫苗中和抗体，似乎从头开始就处于较低水平，甚至在（抵抗）奥密克戎（Omicron）之前就需要加强。先前科兴疫苗三期临牀试验在多国展开，各国试验结果有效性从50% 至90%不等，不过面对奥密克戎变种病毒，世界各国纷纷催打加强针、研究混打效力，何美乡形容疫苗效果是“重新洗牌”。
科兴公司2021年12月公布初步实验结果，称接种三剂科兴疫苗能有效抵御奥密克戎。不过香港大学及香港中文大学医学院12月底发布的联合研究指出，三剂都是接种科兴疫苗的人士，没有足够抗体抵抗奥密克戎。此外，上海交通大学和上海实验室的一项研究也表明，三剂灭活疫苗对奥密克戎的中和活性“显着降低”。
何美乡说：“第三剂要打什麽，这就是要看资料，我们知道它（灭活病毒疫苗）原先是没那麽好，我认为（第三剂）应该打一个比较好的。”她告诉记者，灭活病毒疫苗的效力，从结果看来比信使核糖核酸疫苗低，但仍有防重症、防死亡的效果在，中国可以考虑加强针採取混打方式，譬如和其他中国生产的腺病毒载体疫苗混打，观察是否能够提供更多保护力。
发国难财？科兴2021上半年淨利润51亿
不过，在美股挂牌的科兴生物公司近期披露财报，2021年上半年销售额高达110亿美元，较2020年同期暴增162倍，其中归属股东的淨利润高达51亿美元。根据财务报告，截至2021年12月下旬，科兴生物已在全球提供超过25亿剂疫苗。
“发国难财的人很多，”中国经济学者彭定鼎如此说，“实际执行的时候是强制性打，他赚了很多钱其实是从医保裡赚的钱，国家买单，实际上是全体人民买单。” 彭定鼎说，除了疫苗之外，旅游移动所需的核酸检测和隔离酒店费用，都是人民必须自挑腰包。
中国强制全民接种疫苗的政策，变相给疫苗厂商带来巨大商机，科兴生物财报公布后显示第一大股东是日本软银集团，占股15.07%；第二大股东才是科兴生物CEO尹卫东，持股8.89%，令中国网民吃惊。
彭定鼎反而不在意科兴背后的股东是外资，他表示，若别国有先进技术或丰厚资金，能使中国受利是“绝对没问题”，不过症结点是疫苗的有效性和随之而来的副作用，他认为仍需要经过更缜密的研究。