Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 2 |
Descriptor
Calculus | 3 |
Monte Carlo Methods | 3 |
Simulation | 3 |
Higher Education | 2 |
Mathematical Applications | 2 |
Mathematical Concepts | 2 |
Probability | 2 |
Problem Solving | 2 |
College Mathematics | 1 |
Comparative Analysis | 1 |
Computation | 1 |
More ▼ |
Author
Benakli, Nadia | 1 |
Gordon, Florence S. | 1 |
Gordon, Sheldon P. | 1 |
Ibrahim, A. I. N. | 1 |
Kostadinov, Boyan | 1 |
Mohammed, M. A. | 1 |
Noor, N. F. M. | 1 |
Satyanarayana, Ashwin | 1 |
Singh, Satyanand | 1 |
Siri, Z. | 1 |
Publication Type
Journal Articles | 3 |
Reports - Descriptive | 1 |
Reports - Evaluative | 1 |
Reports - Research | 1 |
Education Level
Higher Education | 1 |
Postsecondary Education | 1 |
Audience
Practitioners | 1 |
Teachers | 1 |
Location
New York | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Mohammed, M. A.; Ibrahim, A. I. N.; Siri, Z.; Noor, N. F. M. – Sociological Methods & Research, 2019
In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to…
Descriptors: Monte Carlo Methods, Calculus, Sampling, Simulation
Benakli, Nadia; Kostadinov, Boyan; Satyanarayana, Ashwin; Singh, Satyanand – International Journal of Mathematical Education in Science and Technology, 2017
The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data…
Descriptors: Calculus, Probability, Data Analysis, Computation

Gordon, Sheldon P.; Gordon, Florence S. – AMATYC Review, 1990
Discusses the application of probabilistic ideas, especially Monte Carlo simulation, to calculus. Describes some applications using the Monte Carlo method: Riemann sums; maximizing and minimizing a function; mean value theorems; and testing conjectures. (YP)
Descriptors: Calculus, College Mathematics, Functions (Mathematics), Higher Education