What problems can a student solve when completing the course?

  1. Take a set of almost-linear data and use a spreadsheet to find the regression line and then do all the same things they would be able to do if the relationship was exactly linear, PLUS use a residual plot to explain why a linear model is appropriate.
  2. Take a set of data which is clearly non-linear and experiment with various non-linear models to find one that fits reasonably well. 
  3. Produce and interpret a residual plot for that.
  4. Use that non-linear model and the graph/  spreadsheet to make predictions of y from x and also to find what x-values give a particular y-value. 
      
  5. Understand that the variability around the line that is shown in the residual plot is “noise” rather than “pattern” and that this noise can often be thought of as measurement noise.