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Course Details
| Course Department: | Department of Mathematics and Statistics |
|---|---|
| Course Code: | MAS 055 |
| Course Title: | Introduction to Probability and Statistics |
| Number of ECTS: | 7 |
| Level of Course: | 1st Cycle (Bachelor's Degree) |
| Year of Study (if applicable): | 2 |
| Semester/Trimester when the Course Unit is Delivered: | Spring Semester |
| Name of Lecturer(s): | Makrides Andreas |
| Lectures/Week: | 2 (1.5 hours per lecture) |
| Laboratories/week: | -- |
| Tutorials/Week: | 1 (1 hours per lecture) |
| Course Purpose and Objectives: | To present to students of computer science basic ideas of probability and statistics which are relevant to computer science |
| Learning Outcomes: | With the completion of the course, the students should have the necessary background and knowledge in probability and statistics and be able to appreciate the applications in their field of computer science. |
| Prerequisites: | Not Applicable |
| Co-requisites: | Not Applicable |
| Course Content: | Probability, conditional probability, Bayes theorem, classical problems of probability (such as balls in bins, birthday problem), random variables, distributions (discrete and continuous), independence, expected values, applications (coupon collector’s problem), probability inequalities (Jensen’s inequality, Markov’s inequality, Chebychev’s inequality, Chernoff bounds), introduction to stochastic processes, Markov chains, applications, random walks, Poisson process, statistics, point estimation, confidence intervals, hypothesis testing, correlation, linear regression. |
| Teaching Methodology: | Lectures and recitation. |
| Bibliography: |
1. T. Christofides: Probability and Statistics (Lecture Notes) 2. R. Hogg and A Craig: Introduction to Mathematical Statistics, Prentice-Hall, 2012 3. M Mitzenmacher and E. Upfal: Probability and Computing, Cambridge University Press, 2005. |
| Assessment: | Midterm exam, homework assignments (in R), final exam |
| Language of Instruction: | Greek |
| Delivery Mode: | Face-To-Face |
| Work Placement(s): | Not Applicable |