This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021. Papers are contributed from established and emerging scholars, covering cutting-edge and contemporary innovative techniques in statistics and data science. Major areas of contribution include Bayesian statistics; computational statistics; data science; semi-parametric regression; and stochastic methods in biology, crop science, ecology and engineering. It will be a valuable edited collection for graduate students, researchers, and practitioners in a wide array of applied statistical and data science methods.

This volume consists of a series of research papers presented at the conference Statistics 2011 Canada: 5th Canadian Conference in Applied Statistics held together with the 20th conference of the Forum for Interdisciplinary Mathematics titled, "Interdisciplinary Mathematical & Statistical Techniques". These papers cover a wide range of topics from applications of Mathematics and Statistics such as Selection Bias in Surveys, Biomarker Discovery, Analysis of Earth Temperature, Supply Chain Management, Trimmed ANOVA, Zero-inflated Data, Non-Gaussian Time Series, and Stochastic Ordering; Classification, Nonparametric Test, and Jackknifed Ridge Estimator; Bayes Factor; Random Graphs and Error Correcting Codes; Meta Analysis; and National Health Plans and Risk Reduction through Supply Chain.The topics have been reviewed by experts in the field and the selected papers are expected to provide a topical resource on the subjects concerned.

This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021. Papers are contributed from established and emerging scholars, covering cutting-edge and contemporary innovative techniques in statistics and data science. Major areas of contribution include Bayesian statistics; computational statistics; data science; semi-parametric regression; and stochastic methods in biology, crop science, ecology and engineering. It will be a valuable edited collection for graduate students, researchers, and practitioners in a wide array of applied statistical and data science methods.