Course Description

Data analysis is major course for students in information and computing science. The main aim of the course is to develop the basic ability of data analysis of students, and enable students to solve problems like regression, classification, clustering and PCA with Matlab software. The study of the course lays foundation for students in data analysis in financial management and for their following scientific research.

Course teaching objective：

The student learning outcomes are what student would be able to know and to do on the completion of this course. In details are:

1.Get to know basic theory of some data analytic methods like regression, classification, clustering, and PCA;

2.Master the demanding mode of those algorithms;

3.Be able to solve simple problems with some data analytic algorithms and demands.

Pre-course

Differential and Integral Calculus, Linear Algebra, Probability and Mathematical Statistics

Textbooks and References

Teaching Materials:

Matlab Data Analysis Methods. Li BaiNian, Wu LiBin, China Machine Press, 2012, Edition 1

References

1.Data Analysis Methods, Fan JinCheng, Mei ChangLin, Higher Education Press,2006.

2.Matlab and Financial Model Analysis. Deng LiuBao. Hefei university of technology press, 2007.

Course Assessment

Form	Weight (%)
Attendance	20%
Experiment	40%
Final exam	40%

Course schedule

Chapter	Content	Period
Chapter 2	Descriptive analysis of data	8
Chapter 3	Regression analysis	8
Chapter 4	Discriminant analysis	8
Chapter 5	Principal component analysis	6
Chapter 6	Cluster analysis	6
Total		36

Weekly	Period	Content
Week 1	4	§Descriptive analysis of data
Week 2	4	§Descriptive analysis of data
Week 3	4	§Regression analysis
Week 4	4	§Regression analysis
Week 5	4	§Discriminant analysis
Week 6	4	§Discriminant analysis
Week 7	4	§Principal component analysis
Week 8	4	§Principal component analysis and cluster analysis
Week 9	4	§Cluster analysis