112年第1學期-1177 資料視覺化分析 課程資訊
評分方式
| 評分項目 | 配分比例 | 說明 |
|---|---|---|
| Attendance and class paticipation | 30 | Students are required to attend class |
| Assignments | 30 | |
| Final project | 40 |
選課分析
本課程名額為 30人，已有10 人選讀，尚餘名額20人。
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授課教師
金泰星教育目標
Graphical Data Analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. It is essential for exploratory data analysis, data mining, and network analysis. The primary focus of this course is to equip students with the necessary knowledge and skills to utilize computer software, such as Python, R, Jamovi, JASP, and Excel, to analyze and visualize data using graphical displays. By using real datasets, students will learn how graphic displays can reveal hidden patterns and trends in data that are not always apparent through traditional statistical methods. The course will cover a range of topics related to Graphical Data Analysis, including data visualization principles, statistical graphics, exploratory data analysis, and data preparation. By the end of the course, students will have a solid understanding of these concepts and will be able to apply them to a variety of real-world data analysis problems.
課程資訊
基本資料
選修課，學分數：3-0
上課時間：一/6,7,8[M023]
修課班級：共選修1-4(管院開)
修課年級：1年級以上
選課備註：全英授課，開放全校學生修習，限30人。
教師與教學助理
授課教師：金泰星
大班TA或教學助理：尚無資料
Office HourOffice hours are to be announced in class. Appointments can also be made with prior arrangements.
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
Textbook
Chang, W. (2018). R graphics cookbook: Practical recipes for visualizing data (2nd ed.). O’Reilly. https://r-graphics.org (Free)
References
The jamovi project. (2022). Jamovi. https://www.jamovi.org/
Navarro, D. J., & Foxcroft, D. R. (2022). Learning statistics with jamovi: A tutorial for psychology students and other beginners. Danielle J.
Navarro and David R. Foxcroft. https://doi.org/10.24384/HGC3-7P15
Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals (1st ed.). Wiley.
Munzner, T. (2014). Visualization Analysis and Design (1st ed.). A K Peters/CRC Press. https://doi.org/10.1201/b17511
Wilke, C. O. (2019). Fundamentals of Data Visualization (1st ed.). O’Reilly Media.
開課紀錄
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