请教各位一个research的基本问题导师给了我一个T or F 的问题
when P is 0.001, meaning there is 1% probability that the null hypothesis is not being true.
我的理解
If P=0.01, so there is a 1% chance that the data groups have no difference while 99% of the chance that the groups have differences. So this is statistically significant as p is less than 0.05.
P value is the probability of getting the results if the null hypothesis is true. So we have a 1% of getting the result if the null hypothesis is true which is no difference.
所以我的答案是 false
然后prof说不对啊，这是基本问题咋答不上来呢。正确答案是true
我之后请教队友，队友跟我理解的还是一样。。
请教了工作友人医生们，还是跟我去理解的一样啊。
难道做了一堆trials发布过N篇papers的也理解错了这个P and Ho吗？
导师还没来得及回答我问题，已经email她。今天我不死心七早八早又找了一堆basic的书，almond ans walker 就说
“the smaller the p value the smaller the likelihood that the null hypothesis is true”...
这也是跟我理解的一样啊。
是在无解，请教各位大神来看看。
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搞不清楚p涵义的学者大把大把的。
顶级期刊基本都出过系列文章来纠正常见的统计学错误，对“唯p马首是瞻”通常是极度痛恨的。
撇开严谨性，答案是false。但如果你写的问题是你导师问题的原话，先不谈T or F，他这个问题的表述的句式就违反了基本的统计学概念。正确的叙述应该是：
When P is 0.01, it means that "the probability is 1% to observe the result obtained assuming the null hypothesis is true".
所有statistical tests只能回答概率，不能证明对错。任何结论都是基于confidence level。撇开CL来解读结果显著性都没任何意义。所以类似于"no difference"的结论性表述都是错误的。正确的表述应该是“no evidence to show the difference"。
撇开严谨性，答案是false。但如果你写的问题是你导师问题的原话，先不谈T or F，他这个问题的表述的句式就违反了基本的统计学概念。正确的叙述应该是：
When P is 0.01, it means that "the probability is 1% to observe the result obtained assuming the null hypothesis is true".
所有statistical tests只能回答概率，不能证明对错。任何结论都是基于confidence level。撇开CL来解读结果显著性都没任何意义。所以类似于"no difference"的结论性表述都是错误的。正确的表述应该是“no evidence to show the difference"。
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