The course intends to meet two goals. It provides tools for empirical work with time

series data and is an introduction into the theoretical foundation of time series models.

Much of statistical methodology is concerned with models in which the observations are

assumed to be independent. However, many data sets occur in the form of time series

where observations are dependent. In this course, we will concentrate on both univariate

and multivariate time series analysis, with a balance between theory and

applications. Students expected to prepare a project report on real life data. After

completing this course, a student will be able to analyze univariate and multivariate time

series data using available software as well as pursue research in this area. In order to

emphasize application of theory to real (or simulated) data, we will use R or SAS.

series data and is an introduction into the theoretical foundation of time series models.

Much of statistical methodology is concerned with models in which the observations are

assumed to be independent. However, many data sets occur in the form of time series

where observations are dependent. In this course, we will concentrate on both univariate

and multivariate time series analysis, with a balance between theory and

applications. Students expected to prepare a project report on real life data. After

completing this course, a student will be able to analyze univariate and multivariate time

series data using available software as well as pursue research in this area. In order to

emphasize application of theory to real (or simulated) data, we will use R or SAS.

- Instructor: Ceylan Yozgatlıgil

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