Statistics II

General

• Code: 205
• Semester: 2nd
• Study Level: Undergraduate
• Course type: Specialization
• Teaching and exams language: Greek
• Teaching Methods (Hours/Week): Lectures (theory) (2) / Laboratory exercises (2)
• ECTS Units: 5
• Course homepage: https://elearning.cm.ihu.gr/course/view.php?id=115
• Instructors: Elekidis Georgios
• Exams Schedule:
  • 05/09/2024, 18:00 - 20:00: Κουρτέση

Course Contents

1. Estimations. Confidence intervals.
2. Statistical hypothesis testing.
3. Goodness of fit tests.
4. Independence Tests and x² distribution.
5. Measuring the relationship between qualitative variables.
6. Pearson’s and Spearman’s correlation coefficient.
7. Hypothesis tests for association in a statistical population.
8. Analysis of categorized data.
9. Basic principles of simple regression.
10. Regression model characteristics.
11. Logarithmic regression.
12. Multiple regression.
13. Solving complex problems with real data.

Educational Goals

The general aim of the course is the understanding and knowledge of the operation of statistical inference with an emphasis on the development of statistical thinking and the ability to analyze quantitative and qualitative data. The application of techniques in the analysis and interpretation of the results of the economy and businesses in the context of both the Greek and the international economic environment, the trends and the demands of the interested parties in terms of the degree of comparability, is also a pursuit, as statistical methods find applications in almost all branches of human activity.

Upon successful completion of the course, students are expected to be able to:

• Use their knowledge and understand issues of generalization of conclusions.
• Perform case checks.
• Have the ability to apply regression methods.
• Use statistical calculus for the analyses.
• Evaluate and compose reports and analyzes that refer to financial management issues.
• Acquire the necessary skills to support the extroverted orientation of agencies and businesses and draw conclusions referring to the data set by using a (small) subset of it.

General Skills

• Working independently.
• Team work.
• Decision-making.
• Production of free, creative and inductive thinking.

Teaching Methods

• In the classroom, face to face.

Use of ICT means

• Basic software (windows, word, power point, the web, etc.).
• Support of learning process through the electronic platform / e-class.

Teaching Organization

Students Evaluation

Theory
Written final exams that may include:

• Judgemental questions.
• Short answer questions.
• Comparative evaluation of theory elements.
• True/False and multiple choice Questions .
• Application exercises.

In each question, corresponding evaluation points are specified.
Optional assignment (Essay writing) corresponds to 40% of the final grade.

Laboratory
The Laboratory part is evaluated on a weekly basis. Prepared assignments covering a specific part of the material each time are distributed and their correct execution is checked for all students. At the end of the semester, all students are tested in a laboratory examination.

Recommended Bibliography

1. Andy Field, Η Διερεύνηση της Στατιστικής με τη Χρήση του SPSS της IBM, Εκδ. Προπομπός, Αθήνα, 2016.
2. Χάλκος Γ., Στατιστική, 4η έκδοση, Εκδόσεις Δίσιγμα ΙΚΕ, Θεσσαλονίκη, 2020.
3. Ζαφειρόπουλος Κ., Μυλωνάς Ν., Στατιστική με SPSS, 2020, Εκδ. Τζιόλα.

Related Research Journals

1. Journal of Business & Economic Statistics.
2. Econometrics and Statistics.
3. Journal of Statistics Education.