101年第1學期-1393 時間序列 課程資訊
|Presentation and Analysis||30|
The objectives of this course are (1) To understand elementary issues of time series data and be able to explain the results coming from time series models. (2) To be able to analyze time series data with conventional time series models and learn relevant statistical methods. (3) To know computational skills required for analyzing time series data.
A time series is a sequence of observations that are arranged according to the time of their outcome. Many recent applications of time series receive much of attention in financial areas. However, time series analysis has also exhibited its importance across many scientific areas for a long history and the desire of such analysis is still going on. This course is to provide introductory lessons in time series for the third and fourth year of undergraduates, who have major interests in statistics, and have finished some elementary courses, such as statistics, calculus, linear algebra and regression. The courses will be in three parts. The first part will be on the focus of regression, including a quick overall review of basics and an extension of regression modeling particularly required for time series data. The second part is aimed at the ARIMA models and seasonal models, which are traditional treatments established by Box and Jenkins. The third part is to introduce some new advances in time series or more real applications of time series models. Served as an undergraduate course, the topics will not be expected to go in great depth but to learn basic approach and to prepare background for further advanced studies.