Target Audience：Undergraduate/Graduate students
This course covers theoretical and applied fundamentals of statistical inference. The primary topics include principles of data reduction, point estimation, hypothesis testing, interval estimation and asymptotic methods.
Understand discrete and continuous random variables, transformations and expectations, common families of distributions, multiple random variables, differential and integral calculus
Casella and Berger. Statistical Inference Second Edition, 2002.
Dr. Fan Yang（F） is a Professor at Yau Mathematical Sciences Center. She obtained her Ph.D. in Applied Mathematics and Computational Science from the University of Pennsylvania in 2014. Dr. Yang’s research interests center around the development of statistical methodologies for causal inference problems inspired by scientific applications, ranging from public health to genomics and educational research. As a first or corresponding author, she has published multiple papers in leading journals in statistics and genetics, including Annals of Applied Statistics, Bioinformatics, Biometrics, Genetic Epidemiology, Genome Biology, Genome Research, and Journal of the Royal Statistical Society Series B. During her PhD study, she received the American Statistical Association (ASA) Section on Statistics in Epidemiology Young Investigators Award in 2013 and ASA Section on Health Policy Statistics Student Paper Competition Award in 2014. She is currently serving as an Associate Editor for Biometrics, one of the leading methodological journals in the biostatistics profession.