Forecasting, Time Series, and Regression

by Bruce L. Bowerman, Richard O'Connell, Anne Koehler

Awarded Outstanding Academic Book by CHOICE magazine in its first edition, FORECASTING, TIME SERIES, AND AN APPLIED APPROACH illustrates the vital importance of forecasting and the various statistical techniques that can be used to produce them. With an emphasis on applications, this book provides both the conceptual development and practical motivation you need to effectively implement forecasts of your own. You'll understand why using forecasts to make intelligent decisions in marketing, finance, personnel management, production scheduling, process control, and strategic management is so vital.

Genres: Science

720 pages, Hardcover

First published April 29, 2004

Reviews

[Nita · Rating 2 out of 5]

What is the likelihood that I will enroll in yet another vaguely quantitative graduate program? If one controls for seasonality, phases of the moon and my menstrual cycle, and factors in frequency of communication with my best friend, average number of cats owned and total count of unpacked boxes in my home, one can engage in some predictive modeling that results in (a) me never finishing my MS in Statistics (2) not enrolling in an MS in Mathematics (c) not even _applying_ to Penn's damned post-bacc to take Calculus I through IV. I might not even finish the calc refresher class I'm _currently_ taking at Berkeley.

Of course, if I'd been able to run that regression in advance of plowing through this book/and the corresponding course [taught by a man whose Indian accent was so thick it was the aural equivalent of seventies bush] I never would've taken said course at t=0. But as with all forecasts, data point n+1 can make all the difference in your model.

In other words, taking a class on regression was a regression, and from here on out, I proclaim, only progressions! (Raise your hand if you've heard _that_ before. Down in front!)

Wait; what? This is only a book for people enrolled in an academic course for credit. It will not look cool on your bookshelf, virtual or otherwise. And taking math classes again in order to provide a skeleton of input/output structure in your otherwise chaotic life is probably a leading indicator that you need to re-engineer things s.t. the amount of chaos approaches zero. QE to the mofo D.

[Kurniati Ratbaputri · Rating 5 out of 5]

I want to read the book as reference for my thesis

[Andreas Engström · Rating 5 out of 5]

If u r into time series so then I would recommend. Otherwise never

[Louis Fan · Rating 4 out of 5]

I came across this book when i was tasked to solve a business problem for my company - how to estimate our target market size using macro economics or industrial indicators. Essentially, this requires carrying out simple or multiple linear regression analysis. My predecessors did not get very far apart from using Excel’s inbuilt regression function to calculate R square correlation coefficient, which was not very useful for our purpose. For me, i also didnt know how to proceed - until i read this book. Using simple and straight-foward language, interspersed with illuminating examples, I was able to not just learn the mechanics of regression analysis - that is to use formulae or statistical software to find the answer, but also understand why things are done in this way. Unlike intro textbook in statistics that often just talk about the statistical theories, what i found useful was the author applied the statisical theory to real life problems. That said, this text is a bit like a manual and is lighter in the theories. So student in statistics may want something more theoretical for their study. For pratitioners, however, this is a gem. Words of caution, to get the best out of the content, I strongly advise that readers have access to statistical software packages. I used a combinatuon of Excel and Minitab often just to see how the results differ. I think having only Excel is definately inadequae as there are certain analysis that simply cannot be done on Excel (well... not easily anyway).