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pearson相关的显著性检验

Pearson相关的显著性检验 (Significance test of Pearson correlation)

  • 相关系数的显著性检验包括两种情况:
  1. 比较样本相关系数r和总体相关系数ρ,推论总体间是否相关;
  2. 比较两个样本相关系数r1和r2,推论它们所属的总体ρ1和ρ2是否有差异。
  • The significance test of the correlation coefficient includes two cases:
  1. Compare the sample correlation coefficient r and the population correlation coefficient ρ to infer whether the population is correlated;
  2. Compare the sample correlation coefficient r1 and another sample correlation coefficient r2 to infer whether the populations ρ1 and ρ2 to which they belong are different.

  • 当对相关方向没有预测时,,我们使用双尾检验,虚无假设和备择假设为: H0: ρ=0,H1: ρ≠0;
  • 当对相关方向有预测时,我们使用单尾检验,虚无假设和备择假设为:H0: ρ≥(≤)0,H1: ρ<(>)0。
  • When there is no prediction of the relevant direction, we use the two-tailed test, the null hypothesis and the alternative hypothesis are: H0: ρ=0,H1: ρ≠0;
  • When there is a prediction of the relevant direction, we use the one-tailed test, the null hypothesis and the alternative hypothesis are: H0: ρ≥(≤)0,H1: ρ<(>)0

  • 两种进行假设检验的方法(Two methods of hypothesis testing):
  1. 根据r值查Pearson相关临界值表(Check Pearson correlation critical value table according to r value);
  2. 计算出t值,查t值临界值表,t值的计算方法如下:

Calculate the t value, check the t value critical value table, the calculation method of t value is as above.

需注意的是查表时的自由度为(n-2)。

Notice: The degree of freedom when looking up the table is (n-2).


pearson相关的显著性检验.txt · 最后更改: 2024/04/11 08:00 由 zzzz