Probability and Statistics for Data Science, written by CDS Associate Professor Carlos Fernandez-Granda, is a hands-on introduction to the two core pillars of data science: probability and statistics. The book explores how these concepts work together, covering everything from random variables and hypothesis testing to principal component analysis and regression techniques. Along the way, readers work with real-world datasets to tackle some of the field’s most important challenges—overfitting, the curse of dimensionality, causal inference, and more.
