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 11:49] – 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 | ||
+ | {{ :: | ||
+ | |||
+ | * 画出交互作用图 | ||
+ | |||
+ | ---- | ||
+ | === 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。 | ||
+ | |||
+ | The decision to accept the null hypothesis is based on the results of the comparison of the calculated individual F values with the corresponding F critical values. | ||
+ | |||
+ | 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)确定显著性水平α | + | 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. |
- | (4)确定临界F值 | ||
- | 这里临界F值有三个,分别是F< | ||
二因素anova的统计过程.1680436166.txt.gz · 最后更改: 2023/04/02 11:49 由 戴娉婷