1. With your previous (or new) bivariate scatter plot, add a regression line.
    • (1 p) plot with regression line,
    • (1 p) label axes and title.
  2. Try plotting the data on a logarithmic scale (\(x\)-only, \(y\)-only, both). What happened to your data when you transformed it?
    • (1 p) At least one logarithmic relationship is plotted, and indicate why you chose this transformation.
    • (1 p) Describe what happened to the relationship (compare original scale to transformed scale).
  3. Does your relationship benefit from a logarithmic transformation?
    • (1 p) Say whether the relationship became more linear with reference to your plots.
  4. Use lm() to fit the linear regression and interpret slope and \(R^2\) (R-squared) values.
    • (1 p) lm summary table is presented,
    • (2 p) slope is interpreted with respect to the increase in the \(y\) variables for each unit increase of the \(x\) variable in the context of the variables in the plot,
    • (1 p) \(R^2\) is interpretted in a sentence.
  5. (1 p) Interpret the intercept. Does it make sense in the context of your study? Can the \(x\)-variable be centered to improve the intercept’s interpretation.