1B013(01734080): Data Analysis Tools and Practice (Spring 2017)


Time: Wednesday 14:00-17:00 Pm

Location: 3205, Teaching Builing, DaXing

Class web site: http://sunhp.org/da2017

Instructor: Huiping Sun (sunhp(at)ss.pku.edu.cn)

TA: Xuwen Han

Course Description

This course will introduces the feature of data analysis with R and RStudio as well as common methods of data analysis based on combination of essential operation experiments and specific case experiments. It covers R and RStudio software, R programming language, R basic graphics methods, data management, data visualization with ggplot2, statical modeling and procedures, and others useful R packages. This course helps students improve the ability of conducting data analysis in related fields independently and finishing analysis report.

Course Textbook

Course Schedule

Date

Topics

Readings

February 22

01. Course Overview [Slides]

March 01

02. R Object I [Slides]]

March 08

03. R Object II [Slides]

  • Textbook. Charpter 4: Basic Data Management.
  • Textbook. Charpter 5: Advanced Data Management.

March 15

04. R Language I [Slides]

  • Textbook. Charpter 2.3: Data Input.
  • Textbook. Charpter 5.4: Control Flow.
  • Textbook. Charpter 5.5: User-written Functions.
  • Data: Data04

March 22

05. R Graphics I [Slides]

  • Textbook. Charpter 3: Getting Started with Graphs.
  • Textbook. Charpter 6: Basic Graphs (6.1-6.3).
  • Hrishi V. Mittal. R Graphs Cookbook. Charpter 1: Basic Graph Functions. PACKET. 2011
  • Hrishi V. Mittal. R Graphs Cookbook. Charpter 2: Beyond Basics: Adjusting Key Parameters. PACKET. 2011
  • Data: Data05

March 29

06. R Graphics II [Slides]

  • Hrishi V. Mittal. R Graphs Cookbook. Charpter 3, 4, 5, 6, 7. PACKET. 2011
  • Data: Data06

April 05

07. ggplot2 I [Slides]

  • Hadley Wickham. ggplot2: Elegant Graphics for Data Analysis. Charpter 1-4. Springer. 2009
  • Winston Cbang. R Graphics Cookbook. Charpter 2-5. O'RELLY. 2013
  • Data: Data07

April 12

08. R Statistics I [Slides]

  • Textbook. Charpter 7: Basic Statistics.
  • Textbook. Charpter 8: Regression.
  • Textbook. Charpter 14: Principal Components and Factor Analysis.
  • Data: Data08

April 19

09. R Statistics II [Slides]

  • Textbook. Charpter 9: Analysis of Variance.

April 26

10. R Packages I: Time Series

[lubridate, forecast, zoo, TSA, TimeSeires]

  • Textbook v2. Charpter 15: Time Series.

May 03

11. R Packages II: String, Word Segmentation, Crawler, etc.

[stringr, Rwordseg&wordcloud2, jiebaR, RCurl, RVEST, glm]

No

May 10

12. ggplot2 II [Slides]

  • Hadley Wickham. ggplot2. Elegant Graphics for Data Analysis. Springer. 2009
  • Hrishi V. Mittal. R Graphs Cookbook. PACKET. 2011
  • Data: Data12

May 17

13. R Packages III:

[quantmod1, quantmod2, ez, reshape2, manipulate, ggvis, shiny]

No

May 24

14. R Packages IV:

[ctree, randomForest, tm, rpart, e1071, nnet, Rhadoop, REmap]

No

Mar 31

15. R Packages V:

[mclust, Rworldmap, leaflet, coin, dplyr]

No

June 7

16. Summary [Slides]

No

Course Grading

The grading scheme is as follows:

Course Projects

Course References