Linear Models (ΣΕΕ2)

Ελληνική Έκδοση
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Department of Mathematics
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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	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	By the end of the course students are expected to demonstrate: A strong foundation in simple linear, multiple regression and in the one- and two-way analysis of variance as well as in extending these concepts, Deep knowledge of the main assumptions of the general linear model and their implications when violated, How to conduct diagnostics and correct for the violation of the assumptions of the general linear model, How to interpret various coefficients and in general how to analyze data with linear models, How to deal with multicollinearity effects, missing data e.t.c..
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

The General Linear Model of full Rank and its statistical properties. Multiple Regression Analysis. Hypothesis tests, diagnostic measures and residual analysis. Variable selection. Models of non full rank. Estimable functions, One and two-way analysis of variance with equal and unequal numbers per cell.

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
Independent study	70
Study and analysis of bibliography, Fieldwork	78.5
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.