UNIVERSITY OF CALIFORNIA, SANTA BARBARA Department of Statistics and Applied Probability PSTAT 174/274, Time Series, Fall 2022
Instructor: Dr. T.A.s:
PSTAT 174/274 is intended for upper-level undergraduate and beginning graduate students interested in methods and the analysis of datasets where data is collected sequentially in time. Such datasets occur in various fields such as economics, insurance, medicine, meteorology, hydrology, electrical engineering, etc.
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Textbooks: Class lectures are self-contained, lecture notes and slides will be posted on the class website each week. Students are encouraged to supplement lectures by reading introductory textbooks on time series. In particular, I will be using the following books:
Introduction to Time Series and Forecasting, by P. Brockwell and R. Davis, Springer.
Time Series Analysis with R Examples, by R. H. Shumway and D. S. Stoffer, Springer.
The textbook is available for free in electronic form UCSB Library. Additional material is available at ’s website http://www.stat.pitt.edu/stoffer/tsa4.
Casualty Actuarial Society (CAS) recommends the following textbook for the time series portion of Exam MAS-I: Introductory Time Series Analysis with R by P. S. P. Cowpertwait and A.V. Metcalfe, Springer. Available for free from UCSB Library.
Course content: Topics include:
– Examples of Time Series. Stochastic Processes
– Stationary Models: Autoregressive and moving average processes (ARMA)
– Non-stationary time series: seasonal data, ARIMA, SARIMA
– Model Building and Forecasting.
– Further topics as time allows: spectral analysis, nonlinear models, financial time series.
Prerequisites: Introductory course on R (PSTAT 10) and on probability and statistics (PSTAT 120A-B or equivalent). These courses must be completed with a minimum grade of C or better.
Recommended Prerequisite: Course on Regression (PSTAT 126 or equivalent)
Course Website: There will be a course website on GauchoSpace. Students are responsible for checking it often. The web and email will be the primary methods of communication.
Assignments: Homework usually will be assigned weekly and collected one week later. Late homeworks will not be accepted. The lowest score will not count when your final homework grade is computed. The assignments will include written problems as well as statistical computations using R (http://www.r-project.org/). Students registered in Pstat 274 will be required to complete additional assigned problems.
Lab assignments will be due weekly and graded P/NP. 75% of an assignment must be completed to receive a Pass. Lab part of the final grade is 0-5%, 5% corresponding to P in all labs but two.
Quizzes: Quizzes will be administered at set dates during the quarter. There will be no make-up quizzes. Tentatively, there will be four quizzes scheduled for Fridays of the weeks 3, 5, 7 & 9 of the class. Changes to these dates, if any, will be posted on Gaucho Space as well as announced in class and via Gaucho Space email.
Final Project: In lieu of final test, students will be required to produce a final project. The project will use the tools developed in this course to analyze a time series data set of the student’s choice. Further project details will be announced later.
Course grades (tentative): 5% Labs, 15% Homework, 30% Quizzes, 50% Final Project.
Academic Honesty and Expected Conduct:
As a University of California student, you have agreed to abide by the University academic honesty policy available at https://studentconduct.sa.ucsb.edu/academic-integrity
In particular, any work submitted to fulfill an academic requirement must represent your original work. You are welcome to discuss approaches to homework problems with other students, but you must write each homework solution on your own (i.e., not copy from another student’s paper, from the whiteboard, etc), and produce your own R code.
Dishonest activities are serious acts which erode the university’s educational and research activities and cheapen the learning experience as well as the value of one’s degree. It is expected that all UCSB students will support the ideal of academic integrity and that they will be responsible for the integrity of their work.
Office hours: Office hours will be conducted via Zoom. Check information on Gaucho Space. Please join in, ask questions and provide feedback on the class. We will also use Nectir chat, check instructions on Gaucho Space.
Ownership of Course Materials: My lectures and course materials, including PowerPoint presentations, tests, outlines, and similar materials, are protected by U.S. copyright law and by University policy. I am the exclusive owner of the copyright in those materials I create. You may take notes and make copies of course materials for your own use. You may also share those materials with another student who is enrolled in or auditing this course.
You may not reproduce, distribute or display (post/upload) lecture notes or recordings or course materials in any other way — whether or not a fee is charged — without my express prior written consent. You also may not allow others to do so. If you do so, you may be subject to student conduct proceedings under the UC Santa Code of Conduct.
Similarly, you own the copyright in your original papers and exam essays. If I am interested in posting your answers or papers on the course web site, I will ask for your written permission.
For more information go to https://copyright.universityofcalifornia.edu/resources/ownership-course-materials.html; https://copyright.universityofcalifornia.edu/resources/recorded-presentations.html
Enjoy the course!
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