Course: Linear statistical models
Code: 3ФЕИТ08011
ECTS points: 6 ECTS
Number of classes per week: 3+0+0+3
Lecturer: Prof. Dr. Katerina Hadji – Velkova Saneva
Course Goals (acquired competencies): Acquiring knowledge about the most popular statistical models and methods, and especially for statistical regression techniques. The student qualifies for the selection of appropriate statistical model, to use software for statistical modeling, as well as for concluding and presenting the results of the statistical analysis of practical problems.
Course Syllabus: Simple linear regression. Confidence intervals and hypotheses testing for model parameters. Generalized linear models. Multidimensional linear regression. Analysis of residues. Analysis of variance. Introduction to linear models for time series. Using statistical software for linear statistical modeling.
Literature:
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Required Literature |
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No. |
Author |
Title |
Publisher |
Year |
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1 |
Ј. P. Marques de Sa | Applied statistics using SPSS, STATISTICA, MATLAB and R | Springer | 2007 |
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2 |
Annette J. Dobson | An Introduction to Generalized Linear Models | CHAPMAN & HALL/CRC | 2000 |
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3 |
Michael H Kutner, Christopher Nachtsheim, John Neter, William Li | Applied Linear Regression Models | McGraw-Hill | 2004 |
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Additional Literature |
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No. |
Author |
Title |
Publisher |
Year |
|
1 |
G.Jay Kerns | Introduction to Probability and Statistics Using R | Cran.r-project.org ISBN: 978-0-557-24979-4 | 2011 |
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2 |
Douglas C. Montgomery, George C. Runger | Applied Statistics and Probability for Engineers | John Wiley & Sons | 2003 |
