Implementation of the projects for the DSC 530: Probability and Statistics for Data Science course, of the MSc in Data Science programme of the University of Cyprus.
The projects mostly focus on fundamental topics of Probability and Statistics in the context of Data Science with its inherent challenges.
Specifically the following topics are covered:
- Fundamental probability topics (random variables, their distribution functions, expected values, conditioning on certain events and independence)
- Etimatation of certain quantities of interest from observations
- Estimators and properties of estimators (sufficiency, unbiasedness and consistency, which enable the evaluation of their quality with an emphasis in the framework of big datasets)
- Different types of hypotheses tests, comparison between tests and how to construct confidence ntervals for their estimators
The implementation contains both the technical report and R-code, and is located in the projects-implementation folder.