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A tentative model

You are handed a data set with measures of the gravitational force between two bodies at different distances and are challenged to build a simple model to predict such force given a specific distance. Initially, you want to stick to simple linear regression. The data consist of 120 pairs of distance and force, and is loaded for you as newton.

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Feature Engineering in R

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Instructions

  • Build a linear model for the newton data using the linear model from base R function and assign it to lr_force.
  • Create a new data frame df by binding the prediction values to the original newton data.
  • Generate a scatterplot of force versus distance using ggplot().
  • Add a regression line to the scatterplot with the fitted values.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Build a linear model for the newton the data and assign it to lr_force
lr_force <- ___(force ~ distance, data = ___)

# Create a new data frame by binding the prediction values to the original data
df <- newton %>% ___(lr_pred = predict(lr_force))

# Generate a scatterplot of force vs. distance
df %>%
  ggplot(aes(x = distance, y = force)) +
  geom____() +
# Add a regression line with the fitted values
  geom_line(aes(y = ___), color = "blue", lwd = .75) +
  ggtitle("Linear regression of force vs. distance") +
  theme_classic()
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