ECTS points: 6 ЕКТС
Number of classes per week: 3+0+0+3
Lecturer: Prof. Dr. Katerina Hadji – Velkova Saneva
Course Goals (acquired competencies): Acquiring knowledge about the basic and commonly used statistical methods and models. Ability to collect data, select appropriate statistical techniques, use software for visualization, analysis and statistical data processing, as well as to draw conclusions and present the obtained results from statistical analysis.
Course Syllabus: Introduction to statistics. Population and sample. Descriptive statistics. Visual representation of data. Point estimates of the unknown parameters. Criteria for quality of estimators. Methods for point estimation. Confidence intervals. Testing of parametric hypotheses. Level of significance and strength of the test. Nonparametric statistical tests. Using software for statistical data processing.
|John A. Rice||Mathematical Statistics and Data Analysis||Cengage Learning||2006|
|Ј. P. Marques de Sa||Applied statistics using SPSS, STATISTICA, MATLAB and R||Springer||2007|
|Douglas C. Montgomery, George C. Runger||Applied Statistics and Probability for Engineers||John Wiley & Sons||2003|
|Ruey S.Tsay||An introduction to Analysis of Financial Data with R||Wiley||2012|
|G.Jay Kerns||Introduction to Probability and Statistics Using R||Cran.r-project.org ISBN: 978-0-557-24979-4||2011|