Session Ready
Exercise

Slopes

During the previous exercise, you used multiple intercepts to model the expected values for discrete groups. During this exercise, you will include continuous predictor variables, slopes, in the model.

Building models for data science is often an iterative process, requiring both visualizing and modeling data.

In this exercise, you will:

  1. Plot the data and build a model that assumes all the data come from one group with the same linear response to the predictor variable x. This model has one slope and one intercept estimate.

  2. Challenge the above assumption. What happens if we model each group with its own intercept?

  3. Go a step farther. What happens if we model each group as having its own slope and intercept?

Instructions 1/3
undefined XP
  • 1
  • 2
  • 3
  • Plot the data, multIntDemo, with x on the x-axis and response on the y-axis. Include a linear model on the plot.
  • Build a linear model using multIntDemo where response is predicted by x.
    Loading