Time Series Analysis Prep for Undergrad | Self-Study Guide

[set]

Hi

I am an undergrad interested in learning time series analysis by himself. Other than the obvious prerequisite courses - 2nd year Calculus and Statistics - what else should I teach myself in prepreation for learning time series analysis?

Thanks

 

[MarneMath]

That's all you need for an introduction. A first year course on probability with calculus and then a follow up course that deals with inference. After that you should be ready to deal with a first course exposure on time series analysis. It probably wouldn't hurt to know r, since a lot of books reference it now a days.

https://www.amazon.com/dp/0387953515/?tag=pfamazon01-20 Here's a fairly basic book that is accessible to an undergraduate. *

*Warning, I've yet to find a 'good' book on this topic at the undergraduate level, so you may find this book hard to follow, not because the subject is difficult, but because the author's writing style. However, the only other books I know are aimed at the graduate level. Maybe someone can recommend something else.

 

[jimmypoopins]

That's all you need for an introduction. A first year course on probability with calculus and then a follow up course that deals with inference. After that you should be ready to deal with a first course exposure on time series analysis. It probably wouldn't hurt to know r, since a lot of books reference it now a days.

https://www.amazon.com/dp/0387953515/?tag=pfamazon01-20 Here's a fairly basic book that is accessible to an undergraduate. *

*Warning, I've yet to find a 'good' book on this topic at the undergraduate level, so you may find this book hard to follow, not because the subject is difficult, but because the author's writing style. However, the only other books I know are aimed at the graduate level. Maybe someone can recommend something else.

That's the book that I studied out of my first year as a graduate student in stat. I think should be easy to follow as a undergrad as long as you have the necessary background.

The other book I have in my collection is Time Series Analysis and Its Applications: With R Examples ( https://www.amazon.com/dp/144197864X/?tag=pfamazon01-20 ). I don't know much about it, but the other book uses an outdated program ITSM for its computation and this book uses R. I've used this one as a reference and it seems good, and according to its amazon page it "is designed as a textbook at both the undergraduate and graduate level and as a reference work for practitioners." I don't know much about the book though, so most of what I'm saying is just observation.

 

[set]

Great Ill take a look at those. Thank you everyone!

 

[MaxManus]

I used the second book, and it is one of the few statistics books i have liked.

 

[Choragos]

I also strongly suggest using Matlab/Octave or Python (or something equivalent) to program up examples. There's nothing like applying a filter and seeing the result immediately to cement the concepts in the books. If you're not familiar with a programming language, I would probably suggest Matlab or Octave (basically a free version of matlab), as it's a bit more intuitive than Python. However, Python has a ton of free signal analysis libraries. There are all kinds of examples out there on the web for download too. Good luck!

Just to add to the library, here are two that I frequently use:
https://www.amazon.com/Time-Analysis-Inverse-Theory-Geophysicists/dp/0521819652/ref=sr_1_1?s=books&ie=UTF8&qid=1354652173&sr=1-1&keywords=time+series+analysis+and+inverse+theory+for+geophysicists (which seems to have become extremely expensive since I bought it), and
https://www.amazon.com/Introduction-Digital-Signal-Processing-John/dp/0123984203/ref=sr_1_1?s=books&ie=UTF8&qid=1354652265&sr=1-1&keywords=an+introduction+to+digital+signal+processing