Mining Data with Probability and Statistics

In this chapter, you will be introduced to the vital world of statistics, which serves as the foundation of applied data science. An understanding of these concepts is crucial for drawing meaningful conclusions and making informed decisions and predictions from data. This knowledge is not just an intellectual exercise; it equips you with essential tools to excel in advanced data science interviews by allowing you to uncover hidden insights within datasets.

This chapter will guide you through the essential aspects of classical statistics, including the analysis of populations and samples, measures of central tendency and variability, and the intriguing realms of probability and conditional probability. You’ll also explore probability distributions, the central limit theorem (CLT), experimental design, hypothesis testing, and confidence intervals. This chapter concludes with a focus on regression and correlation, giving you comprehensive...