Two-way Anova (2)
To conduct a two-way Anova, we can use the exact same functions as when conducting a one-way Anova. This means that both the aov() and lm() functions will work out. When doing a two-way anova, our between-group variance is split across both groups. This essentially means that our first variable will explain a certain amount of variance and our second variable will explain a certain amount of variance.
You can use the aov() with multiple independent variables like so:
aov(dependent_variable ~ independent_variable1 + independent_variable2)
You just have to replace independent_variable1 and independent_variable2 by the names of the variables that you are working with.
This exercise is part of the course
Inferential Statistics
Exercise instructions
- For the current exercise, all our data is available in the dataframe
song_data. Conduct a two-way Anova using theaov()function. Note that you can add variables to your anova by putting a+sign behind your first independent variable followed by the name of the second independent variable. Add the anova model to the variabletwo_way_fit - Call the summary function on your your
two_way_fitobject and print the output to the console.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# run a two-way anove and store it in the object two_way_fit
# call the summary function on the object two_way_fit