Regression and Analysis of Variance (MAE733)

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General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Undergraduate
Course Code	ΜΑΕ733
Semester	7
Course Title	Regression and Analysis of Variance
Independent Teaching Activities	Lectures (Weekly Teaching Hours: 3, Credits: 6)
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 aim of the course is the presentation, study and application of linear models and more precisely the simple and multiple linear regression models and analysis of variance of one or more factors, as well. The general linear model is presented to unify the above mentioned regression and analysis of variance models. This course is focused on the theory of linear models and their applications in modelling statistical data. At the end of the course, students understand the aforementioned issues of the theory of linear models and it is, moreover, expected that they will be able to apply the theory of linear models for the analysis of real statistical data.

General Competences

Working independently Decision-making Production of free, creative and inductive thinking Criticism and self-criticism

Syllabus

Theory of linear models. Simple linear regression. Multiple linear regression. One-and multi-way analysis of variance. Multiple comparisons. 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-Homeworks 33 Course total 150
Student Performance Evaluation	Final written exam in Greek (in case of Erasmus students in English) which concentrates on the solution of problems which are motivated by the main themes of the course.

Attached Bibliography

See the official Eudoxus site or the local repository of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus:

• Kutner, M. H., Nachtsheim, Ch., Neter, J. and Li. W. (2004). Applied Linear Statistical Models. 5 Edition, McGraw-Hill.
• Montgomery, D. C., Peck, E. A. και Vining, G. G. (2006). Introduction to linear regression analysis. 4th Edition, Wiley.
• Rencher, A. C. (2000). Linear models in statistics. Wiley.
• Sahai, H. and Ageel, M. (2000). The Analysis of Variance. Birkhauser.
• Καρακώστας, Κ. (2002). Γραµµικά Μοντέλα: Παλινδρόµηση και Ανάλυση ∆ιακύµανσης. Πανεπιστήµιο Ιωαννίνων.