Computational Statistics Analysis (ΣΕΕ12)

General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Graduate
Course Code	ΣΣΕ12
Semester	2
Course Title	Computational Statistics Analysis
Independent Teaching Activities	Lectures-Laboratory (Weekly Teaching Hours: 3, Credits: 7.5)
Course Type	Specialized general knowledge
Prerequisite Courses	-
Language of Instruction and Examinations	Greek
Is the Course Offered to Erasmus Students	Yes (in English, reading Course)
Course Website (URL)	See eCourse, the Learning Management System maintained by the University of Ioannina.

Learning Outcomes

Learning outcomes	Students completing this course should be able to: Use R and other statistical software to implement computational statistics techniques. Be able to generate random numbers from a variety of distributions and asses their quality. Be able to apply the Jacknife, the Bootstrap and other computational statistics techniques under the appropriate settings and assumptions. Plan and implement a statistical simulation study in an efficient way. Interpret the results from a simulation study.
General Competences	Working independently Decision-making Production of free, creative and inductive thinking Criticism and self-criticism

Syllabus

This course covers the following topics and relies on heavy use of R: random number generation techniques. The jacknife, bootstrap and their theoretical properties. Cross validation, kernel density estimation, local regression. Monte Carlo simulation and its applications.

Teaching and Learning Methods - Evaluation

Delivery

Classroom (face-to-face)

Use of Information and Communications Technology

Use of ICT in communication with students

Teaching Methods

Activity	Semester Workload
Lectures	39
Working independently	78
Exercises-Homework	70.5
Course total	187.5

Student Performance Evaluation

Final written exam in Greek (in case of Erasmus students in English).

Attached Bibliography

Davison, A. C., Hinkley, D. V., (1997). Bootstrap methods and their application. Cambridge University Press.
Rizzo, M. L., (2007). Statistical computing with R. Chapman & Hall/CRC.
Robert, C. P., Casella, G., (2009). Introducing Monte Carlo methods with R. Springer Verlag.
Gentle, J. E., (2009). Computational Statistics, Springer.
Givens, G.H. and Hoeting, J.A., (2012). Computational Statistics, Wiley.
[Περιοδικό / Journal] Statistics and Computing
[Περιοδικό / Journal] Computational Statistics.
[Περιοδικό / Journal] Computational Statistics & Data Analysis.