方法证据记录
P-Value and Statistical Significance
The p-value is the probability of observing data as extreme as or more extreme than what was actually observed, assuming the null hypothesis is true. Introduced by Ronald Fisher in 1925, it is the foundation of frequentist hypothesis testing. Statistical significance is declared when the p-value falls below a pre-specified threshold (alpha level, typically 0.05).
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
P-Value and the Concept of Statistical Significance in Hypothesis Testing
分类方法记录 · process-pipeline / research-statistics
- Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd. · URL
- Neyman, J., & Pearson, E. S. (1933). On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society, 231, 289–337. · DOI 10.1098/rsta.1933.0009
- Wasserstein, R. L., & Lazar, N. A. (2016). The ASA Statement on p-Values: Context, Process, and Purpose. The American Statistician, 70(2), 129–133. · DOI 10.1080/00031305.2016.1154108
精选声明
声明已持久化到证据分类账中,每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时,此视图不会自行创建声明评估。
相关方法
从方法图中生成,显示为机器建议的关系 — 不推断任何证据声明。