Books

Online Resources

• Topics in Statistical Consulting - coauthored with SCSRU at University of Waterloo, 2020.
• A First Course in Statistics - written based on my lecture notes for AFM 113, Spring 2022, at University of Waterloo.
• A Concise Introduction to Survey Sampling - written for STAT 348, Winter 2026, at University of Saskatchewan.

• Van der Vaart, A. W. (2012). Asymptotic Statistics. Cambridge University Press.
• Tsiatis, A. A. (2006). Semiparametric Theory and Missing Data. Springer New York.
• Howell, D. C. (2012). Statistical Methods for Psychology. Cengage Learning.
• Douglas, C. M. (2019). Design and Analysis of Experiments. John Wiley & Sons Ltd.
• McCulloch, C. E., & Searle, S. R. (2008). Generalized, Linear, and Mixed Models. John Wiley & Sons.
• Seber, G. A., & Wild, C. J. (2003). Nonlinear Regression. John Wiley & Sons.
• Särndal, C. E., Swensson, B., & Wretman, J. (2003). Model Assisted Survey Sampling. Springer Science & Business Media.
• Zhao, Q. (2022). Lecture Notes on Causal Inference.
• Neal, B. (2020). Introduction to Causal Inference from a Machine Learning Perspective.
• Van der Laan, M. J., & Robins, J. M. (2003). Unified Methods for Censored Longitudinal Data and Causality. Springer New York.
• Cook, R. J., & Lawless, J. (2007). The Statistical Analysis of Recurrent Events. Springer Science & Business Media.
• Harrer, M., Cuijpers, P., Furukawa, T. A., & Ebert, D. D. (2019). Doing Meta-Analysis with R: A Hands-On Guide.
• Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (1995). Bayesian Data Analysis. Chapman and Hall/CRC.