Linear Models (ΣΕΕ2)

Graduate Courses Outlines - Department of Mathematics

General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Graduate
Course Code	ΣΣΕ2
Semester	1
Course Title	Linear Models
Independent Teaching Activities	Lectures (Weekly Teaching Hours: 3, Credits: 7.5)
Course Type	Special Background
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	The purpose of the course is: the deepening of knowledge of linear models acquired during undergraduate studies the extension of these concepts the presentation of specialized knowledge of Linear Models with applications in statistical data analysis.
General Competences	Working independently Decision-making Adapting to new situations Production of free, creative and inductive thinking Synthesis of data and information, with the use of the necessary technology Working in an interdisciplinary environment

Syllabus

General Linear Model of full Rank, Multiple Regression Analysis, Analysis of residuals-Diagnostics, Selection of Variables, Two way analysis of variance with equal and unequal numbers per cell. Models of non full rank.

Teaching and Learning Methods - Evaluation

Delivery

Face-to-face

Use of Information and Communications Technology

Use of ICT in communication with students

Teaching Methods

Activity	Semester Workload
Lectures	39
Study and analysis of bibliography	78
Preparation of assignments and interactive teaching	70.5
Course total	187.5

Student Performance Evaluation

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

Attached Bibliography

Casella, G. and Berger, R.L. (2002). Statistical Inference. Duxbury Press; 2nd edition.
Mood A. et al. (1974). Introduction to the theory of Statistics. McGraw-Hill.
Roussas G. (1997). A course in Mathematical Statistics. Academic Press.
Hogg, R and Craig, A. (1978). Introduction to Mathematical Statistics.
Lehmann, E.L. and Casella, G. (1998). Theory of point estimation. Springer; 2nd edition
Τ. ΠΑΠΑΙΩΑΝΝΟΥ-Κ. ΦΕΡΕΝΤΙΝΟΥ: Μαθηματική Στατιστική Εκδόσεις Σταμούλη.
Ηλιόπουλος, Γ. (2013). Βασικές Μέθοδοι Εκτίμησης Παραμέτρων. Εκδόσεις Σταμούλη; 2η έκδοση
Bickel, P.J. and Doksum, K.A. (1977). Mathematical Statistics, Basic Ideas and Selected Topics, Vol. 1. Holden-Day.
Rohatgi, V.K. (1976). An Introduction to Probability Theory and Mathematical Statistics. John Wiley and Sons, New York.
Rao, C. R. (1973). Linear Statistical Inference and its Applications. Wiley: 2nd edition.
Lehmann, E.L. and Romano, J.P. (2005). Testing statistical hypotheses. Springer; Third edition, New York.
Van der Vaart (1998). Asymptotic Statistics. Cambridge University Press.