二因素anova的统计过程
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| 二因素anova的统计过程 [2023/04/02 11:50] – 戴娉婷 | 二因素anova的统计过程 [2024/04/14 09:37] (当前版本) – caomingsu | ||
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| - | ==== 二因素方差分析过程 ==== | + | ==== 二因素方差分析过程 |
| ---- | ---- | ||
| - | === 1、陈述假设 === | + | === 1、陈述假设stated hypothesis |
| 二因素方差分析的假设有三: | 二因素方差分析的假设有三: | ||
| - | (1)因素A的主效应:虚无假设为H< | + | Three assumptions were made for the two-factor ANOVA: |
| - | (2)因素B的主效应:虚无假设为H< | + | - 因素A的主效应(Main effect of factor A):虚无假设(null hypothesis)为H< |
| + | - 因素B的主效应(Main effect of factor B):虚无假设(null hypothesis)为H< | ||
| + | - 因素A和因素B的交互作用: | ||
| + | * Interaction of factor A and factor B:The null hypothesis for the interaction is usually stated in words, i.e., the effect of factor A(B) on the dependent variable does not change as a result of changes in factor B(A). | ||
| - | (3)因素A和因素B的交互作用: | ||
| ---- | ---- | ||
| - | === 2、计算相关统计量 === | + | === 2、计算相关统计量 |
| - | (1)自由度的计算{{ :: | + | |
| {{ :: | {{ :: | ||
| {{ :: | {{ :: | ||
| - | + | * 根据公式计算所需的统计量 | |
| - | (2)根据公式计算所需的统计量 | + | |
| {{ :: | {{ :: | ||
| {{ :: | {{ :: | ||
| {{ : | {{ : | ||
| + | * 确定显著性水平α | ||
| + | * 确定临界F值 | ||
| + | // | ||
| + | |||
| + | //Here the critical F-values are three, which areF< | ||
| + | ---- | ||
| + | === 3、计算F统计量 Calculating the F-statistic === | ||
| + | * 根据前面算出的各个值作出如下所示的方差分析表 | ||
| + | {{ :: | ||
| - | (3)确定显著性水平α | + | * 画出交互作用图 |
| - | (4)确定临界F值 | + | ---- |
| + | === 4、得出检验结论 Drawing test conclusions === | ||
| + | 根据算出的各个F值与相应F临界值的比较结果决定是否接受虚无假设。 | ||
| - | 这里临界F值有三个,分别是F< | + | The decision to accept the null hypothesis is based on the results of the comparison of the calculated individual |
| - | ---- | + | 注意当因素之间的交互效应显著时要进行简单主效应分析,即确定一个因素水平,对另一因素的不同水平作单因素ANOVA。 |
| - | === 3、计算F统计量 === | + | |
| + | Note that when the interaction effect between factors is significant a simple main effects analysis is performed, i.e., a factor level is determined and a one-factor ANOVA is done for a different level of another factor. | ||
二因素anova的统计过程.1680436208.txt.gz · 最后更改: 2023/04/02 11:50 由 戴娉婷