05, this tells us that both factors have a statistically significant effect on plant height.Īnd since the p-value for the interaction effect (.201) is not less than. Since the p-value for water and sun are both less than. We can see the following p-values for each of the factors in the table: The first table displays the p-values for the factors water and sun, along with the interaction effect water*sun: Once you click OK, the results of the two-way ANOVA will appear. Drag the following variables into the box labelled Display Means for. In the new window that pops up, drag the variable sun into the box labelled Post Hoc Tests for. The words water*sun will appear in the box labelled Plots. Then click Continue. Drag water into the box labelled Horizontal axis and sun into the box labelled Separate lines. Drag the two factor variables water and sun into the box labelled Fixed Factor: Use the following steps to perform a two-way ANOVA to determine if watering frequency and sunlight exposure have a significant effect on plant growth, and to determine if there is any interaction effect between watering frequency and sunlight exposure.Ĭlick the Analyze tab, then General Linear Model, then Univariate:ĭrag the response variable height into the box labelled Dependent variable. After two months, she records the height of each plant, in inches. She plants 30 seeds and lets them grow for two months under different conditions for sunlight exposure and watering frequency. Example: Two-Way ANOVA in SPSSĪ botanist wants to know whether or not plant growth is influenced by sunlight exposure and watering frequency.
#Two way anova in jmp how to
This tutorial explains how to conduct a two-way ANOVA in SPSS. The purpose of a two-way ANOVA is to determine how two factors impact a response variable, and to determine whether or not there is an interaction between the two factors on the response variable. A two-way ANOVA is used to determine whether or not there is a statistically significant difference between the means of three or more independent groups that have been split on two factors.