Course name: Mathematical software
Course number: SMI2123204     Credit: 2
Course Description:
Mathematical software begins at the third semester, and this course is a professional course of applied mathematics. Through the Matlab software learning, the students should master the basic commands, mapping function, programming language, regression analysis and basic modeling method, which provide software support for subsequent courses calculation method, data analysis.
  
Course Learning Objectives:
The student learning objectives are what student would be able to know and to do on the completion of this course. In details are:
1 Mastering various processing methods of large sample data;
2 Mastering the mapping methods of space curve and curved surface in the space;
3 Mastering the programming methods of conditional statements, the statements of the loop;
4 Learning to solve the integral equations or differential equations;
5 Mastering the Matlab command of multiple linear regression;
6 Mastering the basic methods of parameter estimation and hypothesis testing.
  
Pre-course:  Database application, Mathematical analysis, Advanced algebra
  
Textbooks and References:
Textbooks: Hu Shouxin, Li Bainian. The mathematics experiment with Matlab. Science Press, 2004.
References: Li Jicheng, Dai Yonghong. The mathematics experiment. Xi'an Jiao Tong University press, 2003.
  
Course Assessment:
Form  | Weight (%)  | 
Attendance and homework  | 20%  | 
Mid - term exam  | 0%  | 
Final exam  | 80%  | 
Course schedule:
Weeks  | Teaching content  | Chapter  | 
1-4     | Lecture 1  Processing methods of large sample data 1.The basic   matrix operations 2.The   distance and angle cosine of vectors 3. Property and processing method of data  | Chapter 1  | 
5  | Lecture 2 Mapping of the functions 4. Mapping of the 2-D functions 5. Mapping of the 3-D functions  | Chapter 2  | 
6  | Lecture 3 Programming of Matlab 6. Programming of Matlab   software   | Chapter 3  | 
7-9  | Lecture   4 The numerical analysis method 7. The numerical   solutions of the linear equations and the nonlinear equations 8. Linear interpolation   and surface interpolation 9. Calculation of the   calculus for the function  | Chapter 4  | 
10-13  | Lecture 5  The method of regression   analysis 10. Single-element   regression model 11. Multiple linear   regression model  | Chapter 5  | 
14-15  | Lecture 6 Statistical methods 12. Descriptive statistic 13. Parameter estimation   and hypothesis testing  | Chapter 6  | 
16-17  | Lecture 7 Review   and final exam  |     |