ABSTRACT
A statistician is frequently called upon to estimate the parameters of a simple model from a set of data. The inexperienced statistician can be fooled by the random fall of such data, detecting nonlinear relationships where none exist, finding "peculiar" outliers which are only part of the random noise that might be expected. The exercises in this chapter are designed to provide a "feel" for what might be expected when well-behaved random errors are added to simple models. There are two sets of tables in the chapter. The first set of tables will allow the student to compare a steadily increasing linear response to one that flattens out for large values of the independent variable. The second set of tables will allow the student to search for the linear portion of a response curve which is flat on both ends.
