Statistics
| Title | ΣΤΑΤΙΣΤΙΚΗ / Statistics |
| Code | ΓΕ4000 |
| Faculty | Physical Education and Sport Science |
| School | Physical Education and Sport Science (Serres) |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Winter/Spring |
| Common | No |
| Status | Active |
| Course ID | 260000151 |
Programme of Study: UPS of School of Physical Education and Sports Science in Serres (2014)
Registered students: 115
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | Winter/Spring | - | 3 |
| Academic Year | 2021 – 2022 |
| Class Period | Winter |
| Faculty Instructors | |
| Weekly Hours | 2 |
| Class ID | 600198416
|
Course Type 2016-2020
- Background
- General Knowledge
Course Type 2011-2015
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600198416
- eLearning: https://elearning.auth.gr/course/view.php?id=9716
Language of Instruction
- Greek (Instruction, Examination)
Learning Outcomes
Students are expected uppon the succesive completion of the course:
• To understand the fundamental principles of statistics
• Be able to organize and summarize data numerically and graphically (data and variable categories, measurement scales, histograms, tables, center trend and scatter indicators, frequency distribution description, distribution types)
• To demonstrate the ability to examine the relationship between quantitative data (bar charts, direction and strength of correlation, relationship and cause differences, linear regression)
• To understand the link between probability and statistical inference(experimental and null hypotheses, testing and interpretation of null hypothesis)
• To decide which statistical test to use to examine the relationship between quantitative data, to create a simple regression equation, and to compare the means of two samples: t-test).
• Be able to conduct basic statistical tests using software (descriptive statistics, correlation, regression, comparison of two samples) and interpretate the results.
• To apply the knowledge acquired in the course through their projects.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in teams
- Work in an international context
- Work in an interdisciplinary team
- Generate new research ideas
- Design and manage projects
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction to experimental research, types of data and scales of measurement, frequency distributions for quantitative data, graphs for frequency distributions, typical curves for frequency distributions and normality, averages for quantitative and qualitative data, measures of variability, normal distributions, types of variables, partial correlation, simple linear regression, population and sample, hypothesis testing (null and alternative, level of significance), parametric and non-parametric methods (assumptions and common tests), t-test for two samples.
Keywords
statistics
Educational Material Types
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 20 | 0.8 | ✓ | ||
| Laboratory Work | 6 | 0.2 | ✓ | ||
| Reading Assigment | 50 | 1.9 | ✓ | ||
| Exams | 2 | 0.1 | ✓ | ||
| Total | 78 | 3 |
Student Assessment
Description
The final grade is based on the grades achieved in the final examination. The examination consists partly of multiple choice questions and partly on short-answer questions. Detailed instructions are given to the students at the beginning of the semester in the course outline and in the Depertmrnt's Assignment Manual. Students must achieve at least 50 per cent on the final examination in order to pass the course. During the semester students are able to self-evaluate their understanding on the course material by taking short quizzes.
Student Assessment methods
- Written Exam with Multiple Choice Questions (Formative, Summative)
- Written Exam with Short Answer Questions (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
ΣΤΑΤΙΣΤΙΚΕΣ ΕΦΑΡΜΟΓΕΣ ΣΤΗ ΦΥΣΙΚΗ ΑΓΩΓΗ ΚΑΙ ΣΤΟΝ ΑΘΛΗΤΙΣΜΟ, ΓΕΩΡΓΙΟΣ ΒΑΓΕΝΑΣ, 6η Έκδοση-2018, ΑΘΗΝΑ.
Η ΕΡΕΥΝΑ ΣΤΙΣ ΑΘΛΗΤΙΚΕΣ ΕΠΙΣΤΗΜΕΣ, ΧΡΗΣΤΟΣ ΚΑΜΠΙΤΣΗΣ, ΑΘ. ΤΣΙΑΡΤΣΙΑΝΗΣ Ο.Ε., 2004, ΘΕΣ/ΝΙΚΗ.
Last Update
11-11-2021
