# Time Series Analysis for Data Scientists (Forgy)

- By: Charles Forgy
- Publisher: University of Maryland
- Source: [LibreTexts](https://math.libretexts.org/Bookshelves/Scientific_Computing_Simulations_and_Modeling/Time_Series_Analysis_for_Data_Scientists_(Forgy))
- Licence: [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)
- Read at LibreTexts: https://math.libretexts.org/Bookshelves/Scientific_Computing_Simulations_and_Modeling/Time_Series_Analysis_for_Data_Scientists_(Forgy)
- PDF: https://downloads.libretexts.org/api/v1/download/math-234837/pdf

This book is aimed at students who have a background in a quantitative discipline such as pure data science, physics, electrical engineering, or econometrics. The derivations generally assume at least two semesters of calculus and one semester of linear algebra as well as familiarity with the basics of probability and statistics. More advanced courses such as multi-variate calculus, Fourier analysis, and mathematical statistics are useful but not necessary.