Subject List For Depart

Department of Statistics

Statistics is a broad mathematical discipline which studies ways to collect, summarize, and draw conclusions from data. It is applicable to a wide variety of academic disciplines from physical and social sciences to the humanities as well as to business, government, and industry. Once data is collected, either through a formal sampling procedure or by recording responses to treatments in an experimental setting (experimental design), or by repeatedly observing a process over time (time series), graphical and numerical summaries may be obtained using descriptive statistics.

The major in Statistics was founded in 1990 and has made great developments. Balanced programs for students have been established so that they learn statistical theory as well as practice analyzing data with various statistical computer packages. In order to support independent study, the Department provides two rooms exclusively for a Statistics Library and Computing Lab. The Statistics Library is filled with numerous statistics and computer science books and relevant outstanding papers. The Computing Lab has computers with programs such as SAS, SPSS, S-PLUS, Minitab, MATLAB, and R. The Department has active research programs in statistical genetics, bio-informatics, Bayesian statistics, statistical computing, pattern recognition, and other topics.

Students may seek employment in a number of companies, including major conglomerates, statistical package development firms, life insurance companies, banks, research firms, and the civil service.

Course list

Mathematics 1
Introduction to Statistics and Practice
Mathematical Statistics 1, 2
Regression Analysis and Lab
Statistical Computing and Lab

Discrete Mathematics
Internet, Information Statistics, and Lab
Programming and Mathematics
Computational Statistics and Lab
Design of Experiments
Statistical Quality Control and Lab
Visual Basic Programming and Lab
Sampling Survey Method Theory
C++ Programming and Lab
Official Statistics
Reliability Data Analysis and Lab
Six Sigma Implementing and Lab
Operation System Application and Lab
JAVA and Web Programming and Lab
Time Series Analysis and Lab
Categorical Data Analysis and Lab
Multiplicate Statistical Analysis and Lab
Statistics Database and Lab
Statistical Pattern Recognition
Data Mining and Lab
Statistical Methods in Biometry
Actuarial Science
Statistics Seminar
Statistical Consulting and Practice
Statistical Methods for Clinical Trials

Mathematical Statistics 1, 2
Regression Analysis and Lab

NO	Grade	Term	Subj. No	Point	Subject
1	ALL	ALL	CLT0667	3.0	English for Global Communication 2
2	ALL	ALL	CLT0824	3.0	Scientific Thinking with Big Data
3	ALL	ALL	CLT0936	3.0	Financial Investment in the Big Data Era
4	1	ALL	CLT0771	2.0	Career Plan and Self Understanding
5	1	ALL	CLT0933	3.0	Basic Statistics
6	1	1	BDT0017	3.0	Calculus for Big Data 1
7	1	1	SAI0030	3.0	Python Programming and Practice
8	1	2	BDT0018	3.0	Calculus for Big Data 2
9	1	2	STT1007	3.0	Statistical Packages and Practice
10	1	2	STT9025	3.0	Big Data Programming and Practice
11	2	1	BDT0002	3.0	Machine Learning
12	2	1	BDT0021	3.0	Big Data Computing
13	2	1	BDT0022	3.0	Web Crawling and Big Data Analysis and Practice
14	2	1	STT2007	3.0	Sampling Survey Method Theory
15	2	1	STT3001	3.0	Mathematical Statistics 1
16	2	1	STT9026	3.0	Exploratory Data Analysis
17	2	2	BDT0007	3.0	Financial Mathematics
18	2	2	BDT0019	3.0	Statistical Computing and Simulation
19	2	2	BDT0023	3.0	Statistical Deep Learning
20	2	2	BDT0024	3.0	Big Data Web Programming and Practice
21	2	2	STT2003	3.0	Design of Experiments
22	2	2	STT3005	3.0	Mathematical Statistics 2
23	3	1	BDF0007	3.0	Stock Market Statistical Analysis
24	3	1	BDT0025	3.0	Applied Deep Learning
25	3	1	BDT0026	3.0	Big Data Algorithm
26	3	1	BDT0027	3.0	Survival Analysis
27	3	1	BDT0028	3.0	Statistical Network
28	3	1	STT3017	3.0	Regression Analysis and Practice
29	3	1	STT9022	3.0	Bayesian Statistics and Practice
30	3	2	BDT0012	3.0	Introduction to AI investment
31	3	2	BDT0029	3.0	Statistical Optimization
32	3	2	STT3010	3.0	Multivariate Statistical Analysis and Practice
33	3	2	STT4006	3.0	Data Mining and Practice
34	3	2	STT9004	3.0	Categorical Data Analysis
35	3	2	STT9027	3.0	Financial Statistics and Practice
36	3	2	STT9028	3.0	Big Data Analysis and Practice
37	4	1	BDT0030	3.0	Big Data Numerical Analysis
38	4	1	STT3007	3.0	Time Series Analysis and Practice
39	4	1	STT3029	3.0	Stochastic Processes
40	4	1	STT9006	3.0	Big Data Capstone Design
41	4	2	STT4011	3.0	Statistical Methods in Biometry
42	4	2	STT9013	3.0	Big Data Process and Practice
43	4	2	STT9029	3.0	Statistical Data Analysis and Practice