A/B tests vs. multivariable experiments

The point of an A/B test is that only one thing is changed and the effect of that change is measured. We saw this with our examples in the video and the last few exercises. On the other hand, a multivariate experiment, such as the ToothGrowth experiment from chapter 1, is where a few things are changed (and is similar to a multiple factor experiment, which we covered earlier in this chapter.)

A Lending Club multivariate test can combine all of the explanatory variables we've looked at in this chapter. Let's examine how Group, grade, and verification_status affect loan_amnt in the lendingclub_ab dataset.

Use lm() to examine the effect of all three explanatory variables on loan_amnt. Save as a model object called lendingclub_multi.
Examine lendingclub_multi with tidy() and draw your conclusions.

Exercise

A/B tests vs. multivariable experiments

Instructions