Comparison of Two-Way ANOVA with Multiple Linear Regression

Comparison of Two-Way ANOVA with MLR
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Comparison of Two-Way ANOVA with MLR
A two-way analysis of variance (ANOVA) is usually used in estimating how the mean of a specific quantitative variable changes depending on categorical variables’ levels. For example, an individual can use a two-way ANOVA to identify how a combination of two independent variables influences a particular dependent variable. When gathering data on a certain quantitative dependent variable, where the categorical independent variables change at multiple levels, it is more appropriate to use a two-way ANOVA. On the contrary, a multiple linear regression (MLR) is applied when estimating the relationship between a dependent variable and at least two independent variables. A researcher can use MLR when determining how at least two independent variables relate to one dependent variable. For example, a farmer can use MLR to identify how temperature, amount of fertilizer, and rainfall affect crop production. As such, MLR can predict the outcome of a dependent variable given at least two independent variables.
Specific assumptions are there for ANOVA. First, researchers assume that the