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Data Science Interviews: Probability and Statistics
Topics to study and 20 problems to look over
Overview
Probability and statistics are important areas that every data scientist should know well. At the base of all data analysis lies probability and statistics, which form the foundation for thinking critically about developing and evaluating hypotheses.
By no means should you expect to learn all the topics quickly — many of the topics involve many sub-topics which are in themselves a lifelong journey to study fully, but in general having a strong statistical background is important for the majority of data science interviews. This post will provide some very high level topics and 10 example questions within both topics. The problems discussed are featured from https://datascienceprep.com/ which covers interview questions from top tech companies.
Probability Basics and Random Variables
The beginnings of probability start with thinking about sample spaces, and basic counting and combinatorial principles. Although it is not necessary to know all of the ins and outs of combinatorics, it is helpful to understand the basics and certain methods for simplifying problems. One classic example here is the “stars and bars” counting method.
