The BMJ

Causal inference is hard, and advanced statistical analysis is not enough

Health researchers need to fully understand the underlying assumptions to uncover cause and effect. Timothy Feeney and Paul Zivich explain Physicians ask, answer, and interpret myriad causal questions ...
lse

Statistical Inference: Principles, Methods and Computation

This course is compulsory on the MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan), MSc in Statistics (Financial Statistics) ...
JSTOR Daily

Errata: Bootstrap Statistical Inference: Examples and Evaluations for Political Science

The American Journal of Political Science (AJPS), published four times each year, is one of the most widely-read political science journals in the United States. AJPS is a general journal of political ...
JSTOR Daily

Scalable statistical inference for averaged implicit stochastic gradient descent

Stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates in applications involving large-scale data or streaming data. As an alternative version, averaged implicit SGD ...
lse

Probability, Distribution Theory and Inference

This course is compulsory on the BSc in Actuarial Science and BSc in Financial Mathematics and Statistics. This course is available on the BSc in Data Science, BSc in Econometrics and Mathematical ...
Simon Fraser University

Common Statistical Methods for Clinical Research with SAS Examples

Clinical researchers, with or without a statistical background, will find this book an invaluable aid in understanding the statistical methods cited most frequently in clinical protocols, statistical ...