Content

1. Statistical approach: a brief overview. Useful counting rules (multiplication principle, permutations, k-permutations, combinations).
2. Practical notion of probability; basic probability tools.
3. Conditional probability (multiplication rule; law of the total probability; Bayes theorem); Independence.
4. Random variables (cumulative distribution function; discrete and continuous random variables; probability function; probability density function; mean and variance).
5. Useful discrete distributions (Bernoulli; Binomial; Poisson).
6. Useful continuous distributions (Normal; ; t and F).
7. Central limit theorem. The role of probability in statistics.
8. Descriptive statistics (frequency table; numerical descriptive measures; barchart; piechart; box plot; histograms).
9. Sampling distributions.
10. Estimation; point estimation (properties of an estimator); interval estimation (confidence intervals for a (difference of) population mean (s) or proportion (s));
11. Testing hypotheses for a (difference of) population mean (s) or proportion (s));
12. Analysis of variance (single-factor ANOVA; two-factor ANOVA).
13. Goodness-of-fit test; Chi-Square test of independence.

Learning results

The aim of the course is:

To introduce students to the fundamentals of Probability and Statistics which are relevant to economy and management.

Upon successful completion of the course, the student will be able to:

Distinguishes the basic principles of Probability and Statistics.

using enumeration methods and basic probability tools
describe and summarize data gathered from observing a phenomenon or performing an experiment
apply estimation and testing methods in order to make data-based decisions
identify the selected method’s assumptions and keep in mind that it is required to apply checks for them
critique data-based claims and evaluate data-based decisions
complete a research project that employs simple statistical inference
comply to ethical issues related to data gathering, data usage and publication of results
Understands the basic "tools" for dealing with theoretical and practical problems that arise in the modern business environment.

Bibliography

Suggested bibliography:
•   Χαλικιάς, Ι. Στατιστική, Εκδόσεις Rosili 2017.
•   Παπαδόπουλος, Γ. Κ., Εισαγωγή στις Πιθανότητες και τη Στατιστική, Εκδόσεις Gutenberg, 2015.
•   Κουνιάς, Σ., Κολυβά-Μαχαίρα, Φ., Μπαγιάτης, Κ. και Μπόρα-Σέντα, Ε., Εισαγωγή στη Στατιστική, Εκδόσεις Χριστοδουλίδη, Θεσσαλονίκη 2001.

Related academic journals:
•   Journal of Applied Probability
•   Journal of Statistical Computation and Simulation.

Web Υπηρεσίες

NEWSLETTER

The Department was created in 2019 (article 20, Law 4589/2019) and is an evolution of the Supply Systems Management Department (D.S.E.). Housed in a 770 sq.m. building. within a plot with a total area of 8,000 sq.m. in facilities with extensive research and teaching spaces.