Type of Credit: Partially Required
Credit(s)
Number of Students
This course is an introduction and practice for data analysis for social analysis. In recent years, the application of Big Data has become an important trend in almost every field. This course employs a project-driven strategy that students are able to follow the instructors’ steps about how a data project is developed and how to use R programming to finish a project for academic studies, business analysis, and data journalism.
能力項目說明
There are two sections in this course. The first is R programming’s basic coding skills in 5 weeks. This section will teach basic data mining skills. The second section will provide advanced R coding skills. You are required to develop a research project with your teammates by end of the course. Lastly, this course is designed to provide you with the basic ability to become a member of a professional data analysis team.
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
Week 1: Introduction of the Course (2024/2/22)
Introduction: Data analysis, statistics, and social science
Section 1: Basic R Coding Skills
Week 2: R, Vector, and Object (2024/2/29)
Chapter 1, 2, & 4, Machlis, Sharon. 2019. Practical R for Mass Communication and Journalism. CRC Press
Chapter 1 & 2 in Kabacoff, Robert. 2015. R in Action, Data Analysis and Graphics with R. Manning Publications; 2 Edition
Week 3: Dataframe and Import Data (2024/3/7)
Chapter 4 & 5, Machlis, Sharon. 2019. Practical R for Mass Communication and Journalism. CRC Press
Chapter 4 in Kabacoff, Robert. 2015. R in Action, Data Analysis and Graphics with R. Manning Publications; 2 Edition
Week 4: Advanced Dataframe Manipulation (2024/3/14)
Data-wrangling-cheatsheet
Week 5: Data Mining and Visualization (2024/3/21)
Chapter 6 & 9, Machlis, Sharon. 2019. Practical R for Mass Communication and Journalism. CRC Press
Chapter 7 in Kabacoff, Robert. 2015. R in Action, Data Analysis and Graphics with R. Manning Publications; 2 Edition
Section 2: Advanced R Coding Skills
Week 6: Loop (2024/3/28)
Chapter 5 & 7, Machlis, Sharon. 2019. Practical R for Mass Communication and Journalism. CRC Press
Week 7: Spring Break (2021/4/4)
Week 8: Time Series Analysis (2021/4/11)
Week 9: Midterm Exam (2021/4/18)
Week 10: Form Data Mining to Project Development (2021/4/25)
Week 11: Text Mining (2021/5/2)
Online Lesson：http://regexone.com/
Week 12: Final Project Proposal Presentation (2021/5/9)
Week 13: Geographic Information System (2021/5/16)
Week 14: Web Crawler: Basic (2021/5/23)
Week 15: Table and Dynamic Web Page Scraping (2021/5/30)
Week 16: Final Presentation (2021/6/6)
Week 17: Final Paper Workshop (2021/6/13)
Week 18: Final Paper Writing (2021/6/20)
1. Attendance (10%)
2. Assignments (20%)
3. Midterm exam (25%)
4. Project Proposal (10%)
5. Final Paper (35%)
Generative AI Utility Policy
Conditional Acceptance:
Machlis, Sharon. 2019. Practical R for Mass Communication and Journalism. CRC Press
Kabacoff, Robert. 2015. R in Action, Data Analysis and Graphics with R. Manning Publications; 2 Edition