Introduction to Data Science

Data Science is a scientific field that aims to extract knowledge and insights from data. In inductive practice one is interested to learn about the state of the world given some event, i.e., the data. Data Science is probability theory turned upside down. In this course we will learn about ``estimation'' procedures, in particular, maximum likelihood and the method of moments, and some of their theoretical properties. Furthermore, we learn about hypothesis testing. Then we apply both estimation and testing to a practical setting: linear regression analysis. Regression analysis is at the basis of many more advanced techniques that you will encounter during your Master. We will describe logistic regression as one possible extension.

PREREQUISITES
Introduction to Computational Science

REFERENCES

• Statistical Inference, Casella and Berger, Duxbury, 2th edition.
  Available at https://fsalamri.files.wordpress.com/2015/02/casella_berger_statistical_inference1.pdf.