7.3 P-Value Approach to Hypothesis Testing†
前面步骤同one mean 值，后面计算出H0所对应的概率即为p值,再用p值与significant level相比。
-（2.6+0.05）=-2.65
p值是假如H0假设正确的情况下，得到该值的概率，如果非常小，即在扩大容忍程度的前提下，依然得到偶然值，则说明ho 不被选择，同时满足h1假设（即该值小于H0中的值）
The sample data provide very strong evidence against the null hypothesis (Jack’s claim) and in favor of the alternative hypothesis (Jean’s suspicion)
p是指在该sample情况下，可以容忍的假阴性个数（即The P-value of a hypothesis test is also referred to as the observed significance level.），如果significant level指该h0情况下,可以容忍的假阴性个数，
如果sample情况的假阴性个数小于h0情况下的假阴性个数，则真实情况更严格，则证明h0的情况并非真实情况（以sample作为真实情况的抽样），所以reject H0
如果sample情况的假阴性个数大于h0情况下的假阴性个数，则真实情况更宽松，则证明h0的情况是真实情况（以sample作为真实情况的抽样） ，所以not to reject H0
本质在于：小概率事件不可能发生
不同类型的p-value:
如果是双尾值：
所以：
Using the P-Value to Assess the Evidence Against the Null Hypothesis
we can use the P-value to evaluate the strength of the evidence against the null hypothesis without reference to significance levels.Hypothesis Tests Without Significance Levels: Many researchers do not explicitly refer to significance levels. Instead, they simply obtain the P-value and use it (or let the reader use it) to assess the strength of the evidence against the null hypothesis
