When we considered the decomposition of a Poisson process in the text, weassumed that a generalized Bernoulli trial was performed to select the outputstream an arriving job should be directed to. Let us now consider a cyclic methodof decomposition in which each output stream receives the nth arrival so thatthe first, (n + 1)st, (2n + 1)st, ..., arrivals are directed to output stream 1, thesecond, (n + 2)st, (2n + 2)st, ..., arrivals are directed to stream 2, and so on.Show that the interarrival times of any output substream comprise an n-stageErlang random variable. Note that none of the output streams is Poisson

Chapter 4 Correlation and Linear Regression I will skip Section 7 (Regression to the Mean) and Section 11 (Nonlinear Relationships). You are responsible for the other sections including the What Can Go Wrong and Ethics sections. Response Variable vs. Explanatory Variable (Factor) --- know what they are Scatter Plot to look at the relationship between Two Quantitative Variables Put the Explanatory Variable on horizontal axis and the Response Variable on the vertical axis. The Fit Y by X platform in JMP can be used for everything we do in this chapter. Example 1: Recall the class survey data from Chapter 2 notes. We now look at two of the quantitative variables in that survey. We want to investigate how height (explanatory variable or factor) affects speed (the response var