When there are 3 predictor variables to consider, what is the correct procedure?

Do we make box plots for all the possible 2 combinations or is there a way to compare 3 variables?

Sorry if this is a basic question.

The response is uranium response and there are 3 predictor variables: time, temp, and acid strength. All 3 predictor variables have 3 levels, low, medium, high. I would like to try to run a 3-way ANOVA analysis on the data set, it's an exercise question for a class, but not too sure how to start, so I'm using box plots to see how the data looks like first.

**Contents**hide

#### Best Answer

Thanks for the clarification. You can capitalize on the paneling and clustering designs and put together a compact boxplot like this:

The boxplot will be useful for assessing group-wise distribution and outliers. However, since it's an ANOVA, I'd also recommend visualize the mean and 95% CI as well using error plot:

By comparing and contrasting the positions of each mean and CI across panels and across clusters, one may gain a bit more insight on what the interactions between the group means will be like.

Start from just two variables (uranium vs. temperature, uranium vs. time, etc.) and the build up from there. If your class has not covered interaction yet, then I'd suggest asking the instructor if he/she will allow you to experiment.

### Similar Posts:

- Solved – PCA finds a variable to be the most important twice
- Solved – Boxplot for data with a large number of zero values
- Solved – Analyzing bad lm plots in R (Two parallel lines in Residuals and Normal QQ)
- Solved – Creating marginal plots when using mgcv (GAM) package in R
- Solved – Only binary predictors — ANOVA, regression, or other