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MONTE CARLO SIMULATION WITH R PROGRAMMING LANGUAGE IN TEACHING PROBABILITY AND STATISTICS AT UNIVERSITY LEVEL

MONTE CARLO SIMULATION WITH R PROGRAMMING LANGUAGE IN TEACHING PROBABILITY AND STATISTICS AT UNIVERSITY LEVEL

Le Thi Kim Anh anhltk@buh.edu.vn Ho Chi Minh University of Banking 56 Hoang Dieu 2 street, Linh Chieu ward, Thu Duc city, Ho Chi Minh City, Vietnam
Summary: 
The article aims to use R software to perform Monte Carlo simulations of important concepts and theorems in the subject of Statistical Probability. Based on the author’s teaching experience and knowledge, the Statistical Probability textbooks used in most schools in Vietnam have not focused on simulation methods when presenting the concepts of this subject. This leads to many limitations in students’ learning and understanding, especially difficult concepts such as the concept of confidence intervals, the central limit theorem, and Bayes’s theorem. Using the Monte Carlo simulation method in teaching Probability and Statistics can help students understand the subject’s knowledge both intuitively and intrinsically.
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Keywords: 
onte Carlo methods
probability and statistics.
Refers: 

[1] Matthew J. Sigal - R. Philip Chalmers, (2016), Play It Again: Teaching Statistics With Monte Carlo Simulation, Journal of Statistics Education, 24:3, p.136- 156.

[2] Probability and Statistics for Computer Scientists 3rd Edition, Michael Baron, (2019), Chapman and Hall/ CRC.

[3] Sabrina Luxin Wang - Anna Yinqi Zhang - Samuel Messer - Andrew Wiesner - Dennis K. Pearl, (2021), Student-Developed Shiny Applications for Teaching Statistics, Journal of Statistics and Data Science Education, 29:3, p.218-227.

[4] Doi, Jimmy Potter, Gail Wong, Jimmy et al, (2016), Web Application Teaching Tools for Statistics Using R and Shiny, Technology Innovations in Statistics Education, 9(1).

[5] W. N. Venables, D. M. Smith and the R Core Team, An Introduction to R, Notes on R: A Programming Environment for Data Analysis and Graphics Version 4.1.3 (2022-03-10), https://cran.r-project.org/doc/ manuals/r-release/R-intro.pdf

[6] Michael J. Crawley, (2014), Statistics: An Introduction Using R, 2nd Edition, Wiley.

[7] Reuven Y. Rubinstein, Dirk P. Kroese, (2016), Simulation and the Monte Carlo Method, Wiley. [8] Lê Sĩ Đồng, Giáo trình Xác suất – Thống kê, (2013), NXB Giáo dục Việt Nam.

[8] Bennett, Kevin L., (2018), Teaching the Monty Hall Dilemma to Explore Decision-Making, Probability, and Regret in Behavioral Science Classrooms, International Journal for the Scholarship of Teaching and Learning: Vol. 12: No. 2, Article 13.

Journal: 
No. 9, September 2022

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