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  3. Experimental Design in R

Exercise

Blocking

Though this is not true, suppose the supplement type is actually a nuisance factor we'd like to control for by blocking, and we're actually only interested in the effect of the dose of Vitamin C on guinea pig tooth growth.

If we block by supplement type, we create groups that are more similar, in that they'll have the same supplement type, allowing us to examine only the effect of dose on tooth length.

We'll use the aov() function to examine this. aov() creates a linear regression model by calling lm() and examining results with anova() all in one function call. To use aov(), we'll still need functional notation, as with the randomization exercise, but this time the formula should be len ~ dose + supp to indicate we've blocked by supplement type. (We'll cover aov() and anova() in more detail in the next chapter.)

ggplot2 is loaded for you.

Instructions

100 XP
  • Make a boxplot to visually examine if the tooth length is different by dose. dose has been converted to a factor variable for you.
  • Use aov() to detect the effect of dose and supp on len. Save as a model object called ToothGrowth_aov.
  • Examine ToothGrowth_aov with summary() to determine if dose has a significant effect on tooth length.