Explore the impact of changing the r-statistic steady-state stopping threshold value. You need to define a way to quantify goodness and devise a sufficient number of trials to gather data that is...

Explore the impact of changing the r-statistic steady-state stopping threshold value. You need to define a way to quantify goodness and devise a sufficient number of trials to gather data that is sufficient to make claims. Associated topics are propagation of uncertainty that relates uncertainty on DVs to uncertainty on modeled values. Measures, like FPE, relating to how many model coefficients are justified. The scale-free steady-state stopping criterion is claimed to be right for any model or data variance. Your job is to figure out how to measure appropriate attributes, select test situations that provide legitimate conditions to measure those attributes, do the tests, and evaluate the results. Report what aspect you chose to explore, how you decided to evaluate goodness, how you decided to structure tests and test results, and a discussion about how you know the data appropriately reveals features and permits comparison claims and conclusions.