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  3. Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Exercise

Motorcycle crash data: linear approach

In this first exercise, you will fit a linear model to a data set and visualize the results to see how well it captures relationships in the data. The data set, stored in a data frame named mcycle, contains measurement of acceleration of a crash-test dummy head during a motorcycle crash. It contains measurements of acceleration (g) in the accel column and time (milliseconds) in the times column.

Instructions

100 XP
  • Use the head() and plot() functions to look at the data frame named mcycle.
  • Use the lm() function to fit a model to the mcycle data where the accel variable is a linear function of times.
  • Visualize the model fit using the provided call to termplot().