Course Code & Number
ADA 402
Course Title
Computational Statistics
Level
BS
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 6 ECTS Credits
Year of Study:
Senior
Semester:
Spring
Type of Course:
Elective
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite:
Pre-requisites: MATH 233 OR MATH 232 OR MATH 240 OR MATH 331
Co-requisites: NONE
Catalog Description
Generating Random Variables. Monte Carlo (MC) Method for Statistical Inference. Data Partitioning. Resampling. Bootstrapping. Numerical Methods.
Course Objectives
Proposing computational solutions to problems that cannot be solved analytically. Planning a simulation study. Applying statistical methods based on sampling strategies.
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
1.Develop computational solutions to statistical problems that cannot be solved analytically,
2.Use Monte Carlo methods to solve problems,
3.Plan and implement a statistical simulation study in an efficient way,
4.Learn some of the most common statistical methods based on sampling strategies.
Course Coordinator:
Dr. Seyit Mümin Cılasun