106年第1學期-1760 時間序列 課程資訊
評分方式
評分項目 | 配分比例 | 說明 |
---|---|---|
Homework | 15 | |
Test 1 | 20 | |
Test 2 | 20 | |
Midterm Exam | 20 | |
Final Exam | 25 |
選課分析
本課程名額為 70人,已有67 人選讀,尚餘名額3人。
登入後可進行最愛課程追蹤 [按此登入]。
教育目標
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.
課程概述
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.
課程資訊
基本資料
選修課,學分數:3-0
上課時間:四/4[M024] 四/2,3[M221]
修課班級:統計系2-4
修課年級:年級以上
選課備註:大數據資料群組(105-106適用), A群組(101-104適用)。
教師與教學助理
授課教師:劉家頤
大班TA或教學助理:尚無資料
Office HourBy appointments only. M433.
授課大綱
授課大綱:開啟授課大綱(授課計畫表)
(開在新視窗)
參考書目
Bowerman, O'Connell, and Koehler, 2005, Forecasting, Time Series, and Regression, 4th Ed., Thomson Brooks/Cole
開課紀錄
您可查詢過去本課程開課紀錄。 時間序列歷史開課紀錄查詢