Linear statistical models

Последна измена: December 5, 2019

Course: Linear statistical models

Code3ФЕИТ08011

ECTS points: 6 ECTS

Number of classes per week: 3+0+0+3

LecturerProf. 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:

Required Literature

No.

Author

Title

Publisher

Year

1

Ј. P. Marques de SaApplied statistics  using SPSS, STATISTICA,  MATLAB and RSpringer2007

2

Annette J.  DobsonAn Introduction to Generalized Linear  ModelsCHAPMAN &  HALL/CRC2000

3

Michael H Kutner,‎ Christopher Nachtsheim, John Neter, William LiApplied Linear Regression ModelsMcGraw-Hill2004

Additional Literature

No.

Author

Title

Publisher

Year

1

G.Jay KernsIntroduction to Probability and Statistics Using RCran.r-project.org  ISBN: 978-0-557-24979-42011

2

Douglas C. Montgomery, George C. RungerApplied Statistics and Probability for EngineersJohn Wiley & Sons2003