Probability Theory And Statistics

LEARNING OUTCOMES

The student after the successful completion of the course will be able to:

• Understand the basic mathematical concepts of probability theory and statistics
• Connect the mathematical methodologies taught in the subject of their studies.
• Apply the acquired knowledge in the solution of problems in the field of the Engineer’s specialty.

 

General Competences

• Mathematical thinking and analysis
• Search, analyze and synthesize data with the use of the necessary technology
• Adaptation to new situations
• Decision making
• Autonomous work and Teamwork
• Production of free, creative and inductive thinking

 

SYLLABUS

The course is designed for a set of 13 weeks of lectures and is divided into two main parts. The topics that will be discussed are the following:

1. Probability
   -Introduction to probability theory – basic concepts
   -Random variables
   -Expectation, variance, standard deviation, etc.
   -Probability distribution
   -Discrete and continuous distributions
2. Statistics
   -Basic concepts: population, sample, frequencies, etc.
   -Descriptive statistics
   -Sampling distribution and normal distribution theory
   -Confidence intervals
   -Hypothesis testing
   -Linear regression and correlation

 

STUDENT PERFORMANCE EVALUATION

During the semester students will be given problems- exercises which together with the material of the lectures will be an aid for the preparation of the final exams.

 

ATTACHED BIBLIOGRAPHY

1. Schiller J., Srinivasan R. A., Spiegel, M.R. (2013) – Schaum’s Outline of Probability and Statistics, Mcgraw-Hill, 4th Edition
2. Georgiou, D. (2009) – Probability and Statistics, Kleidarithmos
3. Milonas N. and Papadopoulos B. (2017) -Probability & Statistics for Engineers, Tziola Publications (in Greek)
4. Papageorgiou, E. and Halikias, M. (2020) – Applied Statistics and Probability with SPSS & MATLAB, Broken Hill. (in Greek)