Foundations of Agnostic Statistics

Reflecting changes in empirical research over the past three decades, this book presents the fundamentals of agnostic statistics, which focuses on what can be learned without assuming a true generative model.

It covers estimation theory, regression, maximum likelihood, missing data, and causal inference, providing foundations for inference based on credible assumptions.

Readers can articulate targets of inquiry, distinguish substantive from statistical assumptions, and conduct cutting-edge quantitative research.