STAT 510: Applied Time Series Analysis

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course overview

Time series data are intriguing yet complicated information to work with. While this course will provide students with a basic understanding of the nature and basic processes used to analyze such data, you will quickly realize that this is a small first step in being able to confidently understand what trends might exist within a set of data and the complexities of being able to use this information to make predictions or forecasts. Yet, whether it is financial, medical or weather related, this type of data is quite frequently found in much of our daily lives.

course topics

Topics typically covered in this graduate level course include:

  • Understanding the characteristics of time series data
  • Understanding moving average models and partial autocorrelation as foundations for analysis of time series data
  • Exploratory Data Analysis - Trends in time series data
  • Using smoothing and removing trends when working with time series data
  • Understanding how periodograms are used with time series data
  • Implementing ARMA and ARIMA time series models
  • Identifying and interpreting various patterns for intervention effects
  • Examining the analysis of repeated measures design
  • Using ARCH and AR models in multivariate time series contexts
  • Using spectral density estimation and spectral analysis
  • Using fractional differencing and threshold models with time series data

Here is a link to the Online Notes for STAT 510.

prerequisites

STAT 462 - Applied Regression Analysis, or
STAT 501 - Regression Methods, or
STAT 511 - Regression Analysis and Modeling

textbook

"Time Series Analysis and Its Applications With R Examples", 3rd edition by Robert H. Shumway & David S. Stoffer, © 2012, ISBN: 9781441978646.

(The text is required, though students do not have to purchase it because it is available electronically through the Penn State library.)

software

This course makes extensive use of the R Statistical Software. This is open-source free software that can be downloaded from the R Project home page. For more information and links to download this software please see the Statistical Software page. MS Word is also required.

R involves programming. Students should already feel comfortable using R at a basic level, be a quick learner of software packages, or able to figure out how to do the required analyses in another package of their choice. Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit course in R in order to establish this foundation before taking STAT 510.

R will be supported and sample programs will be supplied but you will be required to do some programing on your own. Due to different software applications, software versions and platforms there may be issues with running code. Students must be proactive in seeking advice and help from appropriate sources including documentation resources, other students, the teaching assistant, instructor or helpdesk.

assessment plan

Lab / Homework Activities - will be given weekly.  In order to receive credit for homework, all assignments must include HOW an answer is obtained, not just the numerical solution. These assignments can be compiled in Word, however, submission as a .pdf is prefered.

Exams - There will be one mid-term and one final exam. These are 'take-home' application oriented exams that should be completed in the time specified by the instructor.

academic integrity

All Penn State policies regarding ethics and honorable behavior apply to this course. Academic integrity is the pursuit of scholarly activity free from fraud and deception and is an educational objective of this institution. All University policies regarding academic integrity apply to this course. Academic dishonesty includes, but is not limited to, cheating, plagiarizing, fabricating of information or citations, facilitating acts of academic dishonesty by others, having unauthorized possession of examinations, submitting work of another person or work previously used without informing the instructor, or tampering with the academic work of other students.

For any material or ideas obtained from other sources, such as the text or things you see on the web, in the library, etc., a source reference must be given. Direct quotes from any source must be identified as such.

All exam answers must be your own, and you must not provide any assistance to other students during exams. Any instances of academic dishonesty WILL be pursued under the University and Eberly College of Science regulations concerning academic integrity. For more information on academic integrity, see Penn State's statement on plagiarism and academic dishonesty.

The Eberly College of Science Code of Mutual Respect and Cooperation embodies the values that we hope our faculty, staff, and students possess and will endorse to make The Eberly College of Science a place where every individual feels respected and valued, as well as challenged and rewarded.

disabilities

Penn State welcomes students with disabilities into the University's educational programs. If you have a disability-related need for reasonable academic adjustments in this course, contact the Office for Disability Services (ODS) at 814-863-1807 (V/TTY). For further information regarding ODS, please visit the Office for Disability Services Web site at http://equity.psu.edu/ods/.

In order to receive consideration for course accommodations, you must contact ODS and provide documentation (see the documentation guidelines at http://equity.psu.edu/ods/guidelines/documentation-guidelines). If the documentation supports the need for academic adjustments, ODS will provide a letter identifying appropriate academic adjustments. Please share this letter and discuss the adjustments with your instructor as early in the course as possible. You must contact ODS and request academic adjustment letters at the beginning of each semester.

course author

Dr. Megan Romer is the current author of the materials used in this course. The material builds on that of the course's previous authors, Robert Heckard and John Fricks.