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| {{Infobox nodebasic
| | #Redirect [[Two_Way_ANOVA]] |
| |nodename=Two_Way_ANOVA
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| |nodeimage=Two Way ANOVA.png
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| |icon=Two Way ANOVA.svg
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| |simpleicon=Two Way ANOVA_Pure.svg
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| |developer=Dev.Team-DPS
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| |productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用
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| |productionstatedesc=在[[Update:DecisionLinnc 1.0.0.8|V1.0]]部署
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| |nodeenglishname=[[Has english name::Two Way ANOVA]]
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| |abbreviation=[[Has abbreviation::ANOVAT]]
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| |funcmaincategory=数据分析
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| |funcsubcategory=[[DataAGM Lv1 Cat::方差分析]]
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| |nodecategory=数据挖掘
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| |nodeinterpretor=R
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| |nodeshortdescription=<p>Two-Way-ANOVA也称为双因素方差分析, 用来分析两个因素的不同水平对结果是否有显著影响,以及两个因素之间是否存在交互效应。分析前的假设是随机采样, 样本独立, 符合或接近正态分布, 和残差方差要一致。</p><p>用途:用于研究两个独立变量(称为因素)对一个连续型因变量的影响。</p><p>参数:选择正态分布数值因变量,和两个自变量因素</p>
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| |nodeinputnumber=5
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| |nodeoutputnumber=2
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| |nodeloopsupport=是
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| |nodeifswitchsupport=否
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| |nodeavailableplotlist=ScatterCloudsAndRainPlot;twoanovagraphPlot;SpittingPointLinePlot
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| |nodeavailabletablelist=df;MSE;F-Value;PES;P-Value
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| |nodeconfiguration=VariableList
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| |nodeinputports=WorkFlow-Control ➤;Transfer-Variable ◆;Transfer-Table ■
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| |nodeoutputports=WorkFlow-Control ➤;Transfer-Table ■
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| |statsapewikiurl=https://wiki.statsape.com/Two_Way_ANOVA
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| |previousnode=[[One_Way_ANOVA]]
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| |nextnode=[[多重比较方差分析]]
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| }}
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| {{Navplate AlgorithmNodeList}}
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| [[Category:方差分析]]
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