I hope this message finds you well.
This is an online bookdown file, which we plan to update regularly with the class material. We suggest that you to write the code simultaneously with us at seminar, but bugs can always occur out of the blue… If you missed something or just want to revisit the topic with additional comments (probably before the exam day) this page is here to help.
At the end of the course you should know:
What are data types, data quality, and data preprocessing?
What are the components of
tidyverseand what are their advantage?
What are density, distribution function, quantile functions?
How to scrape from the web?
How to impute missing data?
What are the main techniques for simulation?
We will work with
R, one the most loved statistical programming language. Do not be afraid if you do not have any programming experience, this is a beginner course. However, by the end of the program, we hope you will find useful the concept and practical tips we offer, and you will be able to solve your own real life data analysis issues.
Gábor Békés & Gábor Kézdi: Data Analysis: Patterns, Prediction and Causality