Statistics
General
Code: ΜΥ04
Language: Greek
Delivery: Face-to-face
Prerequisites:
Workload
- Lectures: 39.0 hours
- Lab: 13.0 hours
- Study: 98.0 hours
- Project: 0.0 hours
Course Content
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 Outcomes
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.
Skills
Search, analysis and synthesis of data and information
Adaptation in new conditions
Decision Making
Independent work
Work at an interdisciplinary framework
Formulation of new research ideas
Promoting reasoning and self improvement
Promoting free, creative and deductive reasoning