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Basic Data Analysis for Time Series with R by DeWayne Derryberry

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ACKNOWLEDGMENTS

First and foremost, I must acknowledge the patient and gracious students who took my classes: Jeremy Farrell, Michael Chow, Megan Loveland, Anthony Lock-Smith, Gee Mellisa Pricilia, Yevgeniy Ptukhin, Christie Solomon (Spring 2011); Theo Barnhart, Leland Davis, Meghan Fisher, Noelle Guernsey, Michael Jacobson, Andrew Jensen, Christopher Tennant, Tyler Yazzie, Ted Owens, Garrett Castle, Anthony Wilson (Fall 2012). Students who take a class based only on notes have a difficult task. There is no table of contents, nor is there an index. Notes are full of errors, typos, and graphs with poor labeling. Page numbers are in constant flux. Sometimes, the students get to follow the instructor down dead ends (if properly done, this really is a good way to teach mathematics). On the other hand, for those who can handle a heavy cognitive load, there is something to be said for learning with the instructor instead of learning from the instructor. Garrett Castle also worked for me one school year helping get the book in the final form.

A number of colleagues have been helpful in different ways. My chair, Bob Fisher, has been very helpful in scheduling so that I could teach the course twice and get the book written. Greg Snow would not know me, but he taught at the 2.5-day workshop that I attended on R at Brigham Young University in the summer of 2013, and this was extremely helpful.

Certainly, at some level, this book would never have the great data sets without the Time Series ...

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