ΜΥ04 - Statistics
School: Digital Technology
Department: Informatics and Telematics
Course Title: Statistics
Course id: ΜΥ04
Type: Background Course
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: http://eclass.hua.gr/courses/DIT142/
Lectures (Theory): 3,0
Lab lectures: 2,0
ECTS credits: 5,0
The objective of the course is to be well prepared for problem-solving involving statistics in the rest of your courses, as well as gaining an understanding of the role of statistics in your daily life.
Search, analysis and synthesis of data and information
Adaptation in new conditions
Work at an interdisciplinary framework
Formulation of new research ideas
Promoting reasoning and self improvement
Promoting free, creative and deductive reasoning
1. Elements of Descriptive Statistics: Population, Samples, Random Samples, Descriptive Measures, Frequency and Relative Frequency Tables, Plots of Empirical Frequency Distributions
2. Applications of Descriptive Statistics relative to Science of informatics and Telematics, lab exercises with R language
3. Statistical Inference: Point Estimation, Confidence Intervals of population parameters
4. Statistical Inference: Hypothesis Testing of population parameters
5. Applications of Statistical Inference relative to Science of informatics and Telematics, lab exercises with R language
6. Correlation and Linear Regression
7. Analysis of Variance
8. Applications of Linear Regression and Analysis of Variance relative to Science of informatics and Telematics, lab exercises with R language
9. - Independence Test
10. - Goodness of Fit Test
11. - Homogeneity Test
Applications of relative to - Homogeneity Test, lab exercises with R language
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Use of R language. Support the learning process through the electronic platform e-class
The evaluation of each student will be made with writing exams and/or interim written exams.
- A. Kyriakoussis (2000). Statistical Methods, Symmetria Editions, Athens.
● S. Loukas (2003), Statistics. Kritiki Editions.
● M. Filippakis (2017). Statistical Methods and Regression Analysis for New Technologies. Tsotras Edistions.