Regression and Analysis of Variance (MAE733): Διαφορά μεταξύ των αναθεωρήσεων
Χωρίς σύνοψη επεξεργασίας |
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Γραμμή 100: | Γραμμή 100: | ||
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=== Attached Bibliography === | === Attached Bibliography === | ||
See [https://service.eudoxus.gr/public/departments#20 Eudoxus]. Additionally: | |||
* Kutner, M. H., Nachtsheim, Ch., Neter, J. and Li. W. (2004). Applied Linear Statistical Models. 5 Edition, McGraw-Hill. | * 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. | * 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. | * Rencher, A. C. (2000). Linear models in statistics. Wiley. | ||
* Sahai, H. and Ageel, M. (2000). The Analysis of Variance. Birkhauser. | * Sahai, H. and Ageel, M. (2000). The Analysis of Variance. Birkhauser. | ||
* Καρακώστας, Κ. (2002). Γραµµικά Μοντέλα: Παλινδρόµηση και Ανάλυση ∆ιακύµανσης. Πανεπιστήµιο Ιωαννίνων. | |||
* Καρακώστας, Κ. (2002). Γραµµικά Μοντέλα: Παλινδρόµηση και Ανάλυση ∆ιακύµανσης. Πανεπιστήµιο Ιωαννίνων. | |||
Αναθεώρηση της 12:54, 23 Ιουλίου 2022
Undergraduate Courses Outlines - Department of Mathematics
General
School |
School of Science |
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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) | http://users.uoi.gr/kzograf/SyllabousRegressionEnglish.pdf |
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. |
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General Competences |
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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) | ||||||||||
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Use of Information and Communications Technology | Use of ICT in communication with students | ||||||||||
Teaching Methods |
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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 Eudoxus. Additionally:
- 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.