pearson相关的显著性检验
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| pearson相关的显著性检验 [2023/04/06 05:58] – 戴娉婷 | pearson相关的显著性检验 [2024/04/11 08:00] (当前版本) – zzzz | ||
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| - | ==== Pearson相关的显著性检验 ==== | + | ==== Pearson相关的显著性检验 |
| - | 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; | + | - 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; |
| + | - 比较两个样本相关系数r< | ||
| - | 2、比较两个样本相关系数r< | + | * The significance test of the correlation coefficient includes two cases: |
| + | |||
| + | - Compare the sample correlation coefficient r and the population correlation coefficient ρ to infer whether the population is correlated; | ||
| + | - Compare the sample correlation coefficient | ||
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| - | 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:H< | + | * 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: H< |
| - | 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:H< | + | * 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:H< |
| - | ---- | + | * When there is no prediction of the relevant direction, we use the two-tailed test, the null hypothesis and the alternative hypothesis are: H< |
| - | 进行假设检验的方法有两种: | + | * When there is a prediction of the relevant direction, we use the one-tailed test, the null hypothesis and the alternative hypothesis are: H< |
| - | 1、根据r值查Pearson相关临界值表; | + | ---- |
| + | |||
| + | * 两种进行假设检验的方法(Two methods of hypothesis testing): | ||
| - | 2、计算出t值,查t值临界值表,t值的计算方法如下: | + | - 根据r值查Pearson相关临界值表(Check Pearson correlation critical value table according to r value); |
| + | - 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. | ||
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| 需注意的是查表时的自由度为(n-2)。 | 需注意的是查表时的自由度为(n-2)。 | ||
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| + | Notice: The degree of freedom when looking up the table is (n-2). | ||
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pearson相关的显著性检验.1680760726.txt.gz · 最后更改: 2023/04/06 05:58 由 戴娉婷