Instructor:                 รศ. ดร.วีระชาติ กิเลนทอง (tee@riped.utcc.ac.th)

Course Schedule:       Saturday 9.00 am – 12.00 pm Room 5602

TAs:                               ดร.สัจจา ดวงชัยอยู่สุข  (kei@riped.utcc.ac.th)

This course studies basic probability and statistical theory concepts relevant to financial engineering. The topics include basic probability, conditional probability, random variables and their distributions, expectation and moments, special distributions, asymptotic theory and properties of large random samples, point estimation and maximum likelihood estimation, sampling distributions of estimators, hypothesis testing, linear statistical models, and basic nonparametric methods.

1.     Course Objective

This course aims to introduce master-level students to principles, theories, and tools in basic statistical theory. Students will also learn how to apply statistical models with actual data using STATA software.

3.     Required Textbooks:

1. DeGroot, Morris H. and Mark J. Schervish. 2012. Probability and Statistics. 4th edition: Preason. [DS]

2. Hogg, Robert V., Allen T. Craig and Joseph W. McKean. 2005. Introduction to Mathematical Statistics. 6th edition, Pearson. [HCM]

3. Wooldridge, F.M. (2020). Introductory Econometrics: A Modern Approach (7th Edition). CENGAGE. [W] 

Optional Textbooks:

1. Ross, S. M. (2014). Introduction to Probability Models. Academic press.

Data Sources

        We will provide relevant data through the course website: https://sites.google.com/riped.org/tee/teaching/statistics

Program Sources

Program STATA version 18

4.     Grades and Requirements

Grades will be based on the following weights:

30%         Assignment(s)

30%         Mid-Term Exam  

40%         Final Exam          

Tentative Grading Range:

85 – 100   A

80 – 84     B+

70 – 79     B

65 – 69     C+

55 – 64     C

50 – 54     D+

40 – 49     D

39 or less F

             4.1. Assignment

Students will be assigned to complete 14 individual assignments during the semester. An assignment with the lowest score will be dropped when the total score for each student is calculated. Note: Late submission of the assignments is not accepted; a score of zero will be recorded for that assignment.

            4.2. Examination

There will be two examinations: a mid-term exam counting for 30% of the total points and a final exam counting for 40% of the total points. If a student misses a regular examination without an acceptable excuse, a score of zero will be recorded for the examination. 

Course Schedule

The course will be in 15 sessions, totaling 45 lecture hours. If necessary, the course structure is subject to revision (e.g., to conform to the student's background, knowledge, and interests). The tentative schedule of the whole course is as follows:

1. Week 1 (August 15, 2026) :  Basic Probability Theory. Lecture Note; STATA Code; Data.

2. Week 2 (August 22, 2026) :  Conditional Probability. Use the same Lecture Note as Week 1.

3. Week 3 (September 5, 2026) :  Random Variables and Probability Distributions. Lecture Note

4. Week 4 (September 12, 2026) :  Joint Distributions and Conditional Distributions.

5. Week 5 (September 19, 2026) :  Statistical Independence and Distribution of Function of Random Variables.

6. Week 6 (September  26, 2026) : Expectation and Variance of Random Variables.

7. Week 7 (October 3, 2026) : Covariance, Correlation, and Moments. 

8. Week 8 (October 10, 2026) : Conditional Expectation. 

9. October 17, 2026 : MIDTERM EXAM (9.00 am to 12.00 pm) Covering Week 1-7

10. Week 9 (October 24, 2026) : Normal Distributions and Popular Distributions.

11. Week 10 (October 31, 2026) : Large-Sample Theories. 

12. Week 11 (November 7, 2026) : Point Estimation: Bayes and MLE Estimations.

13. Week 12 (November 14, 2026) : Hypothesis Testing

14. Week 13 (November 21, 2026) :  Regression Model: Estimation

15. Week 14 (November 28, 2026) :  Regression Model: Inference

16.  November 28, 2026 : Final EXAM (9.00 am to 12.00 pm)

Problem Assignments

1. Problem Assignment 1 (Due on August 22, 2026, at the beginning of the class). Solution

2. Problem Assignment 2 (Due on September 5, 2026, at the beginning of the class). Solution

3. Problem Assignment 3 (Due on September 12, 2026, at the beginning of the class).

Computer Codes

1. STATA Code Lecture 1.

2. STATA Code Lecture 2.

3. STATA Code Lecture 3.