1. GENERAL
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SCHOOL |
SCHOOL OF ECONOMIC SCIENCES |
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ACADEMIC UNIT |
DEPARMENT OF ACCOUNTING AND FINANCE |
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LEVEL OF STUDIES |
Undergraduate |
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COURSE CODE |
BA203 |
SEMESTER |
1 | ||
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COURSE TITLE |
APPLIED STATISTICS | ||||
| INDEPENDENT TEACHING ACTIVITIES |
WEEKLYTEACHING HOURS |
CREDITS | |||
| Lectures | 3 | ||||
| Hours Lab | 0 | ||||
| Hours Exercises | 0 | ||||
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Total |
3 | ||||
| COURSE TYPE | Scientific Field, Compulsory | ||||
| PREREQUISITE COURSES | BA103 Introduction to Statistics | ||||
| LANGUAGE OF INSTRUCTION and EXAMINATIONS | Greek | ||||
| IS THE COURSE OFFERED TO ERASMUS STUDENTS | Yes (upon request) | ||||
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COURSE WEBSITE (URL) |
https://
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2. LEARNING OUTCOMES
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Learning outcomes |
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After successful completion of the course, students are expected to be able to: 1. Have knowledge of the concepts and theories of estimating models 2. Have knowledge of the basic statistical techniques for testing hypotheses in ANOVA, simple and multiple regression, nonlinear regression 3. Have knowledge of the estimation methods for limited dependent variable models 4. Have knowledge of the basic principles of time series models 5. Be able to insert and analyze data using statistical analysis techniques in the statistical packages Eviews and Gretl 6. Know how to apply statistical methods in practice |
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General Competences |
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• Decision-making • Autonomous work • Group work |
3. SYLLABUS
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The course aims at introducing the student to advances concepts and tools of statistical analysis, as well as statistical applications in business and finance. The analysis of Variance (ANOVA) techniques is presented, together with non-parametric methods, simple and multiple linear regression, nonlinear regression, and hypothesis testing in all these models. An introduction to time series models concludes the course. The coursecontentincludes: • Review of basic statistics methods (statistical measures, confidence intervals, testing hypothesis) • Statistical analysis using Excel, Eviews and Gretl • Non-parametric methods • Analysis of variance (ANOVA) • Simple linear regression – assumptions – violations of assumptions • Multiple regression – nonlinear regression • Limited dependent variable models • Introduction to time series analysis • Application of the above models in economics, business and finance using Eviews and Gretl |
4. TEACHING and LEARNING METHODS - EVALUATION
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DELIVERY |
Face to face | ||||||||||||||||||||||||
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USE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY |
Use of the electronic platform e-class During office hours Presentations are made using Power Point. There is also the possibility of electronic communication via e-mail to the teacher. Providing electronic teaching presentations to Students, via e-class |
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| TEACHING METHODS |
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STUDENT PERFORMANCE EVALUATION |
• Mid-term Exam 30% • Final Exam(multiple choice, short-answer questions, problem solving) 70% |
5. SUGGESTED BIBLIOGRAPHY
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Recommended Book Resources: • Σαριαννίδης Νικόλαος, Γεώργιος Κοντέος, Ανάλυση δεδομένων και μεθοδολογία έρευνας, Εκδόσεις Αλέξανδρος 2019 • Ταγαράς Γ. Ν., 2001. Στατιστικός Έλεγχος Ποιότητας. Εκδόσεις Ζήτη. [ISBN: 960-431-706-7] • Gourieroux, C., Monfort, A. & Vuong, Q. (1995) Statistics and econometric models, Cambridge University Press, ISBN: 978-0521478373 • Borak, S., Wolfgang, H., & López Cabrera, B. (2013) Statistics of Financial Markets, Sprigner, ISBN : 978-3642339288 |
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-Related academic journals: |