The Applied Statistics discipline at the College of Science, Northeast Forestry University, integrates modern forestry development with societal demands, adapts to the needs of socialist modernization with Chinese characteristics in the new era, and serves national and regional economic-social development. Grounded in modern statistical theories and advanced analytical methods, it combines statistics with related interdisciplinary fields to cultivate high-level applied professionals with strong political integrity and professional ethics. These talents systematically master solid statistical ideologies, theories, and methodologies; possess robust capabilities in scientific research and technical skill expansion; demonstrate practical operational competencies in statistical data collection, organization, analysis, prediction, and application; and exhibit comprehensive qualities. They are qualified to engage in statistical applications and data analysis across industries, including socio-economics, financial statistics, risk management, and big data analytics, as well as in government agencies, enterprises, institutions, and fields such as natural sciences, humanities, engineering, and medicine.

Rooted in the Mathematics Department established in 1980 and the Probability & Mathematical Statistics sub-discipline under the first-level mathematics discipline founded in 2010, this discipline leverages its strong theoretical and practical foundation in statistics to build an academic team with a rational structure and broad research scope. Significant achievements have been made in stochastic biological modeling, statistical inference of parameters, reliability statistical analysis, applied multivariate statistical analysis, uncertainty in deep learning, image processing, and data mining. Through interdisciplinary collaboration with the university's Double First-Class initiative disciplines, it integrates research with forestry, ecology, and forest engineering, demonstrating distinctive advantages in forest fire prediction, wood material testing, and stand growth studies, with some models already applied in practical production. Current research directions include Statistical Model Application and Big Data Analysis.

(1)Statistical Model Application: This direction focuses on fundamental statistical theories/methods, qualitative variable analysis, and comprehensive statistical evaluation/application. Supported by statistical theories and methodologies, it cultivates applied statistics professionals with comprehensive qualities for biostatistics, financial statistics, forestry statistics, statistical optimization, educational measurement, and related fields.

(2) Big Data Analysis: This direction investigates prominent data analysis theories and technical methods, supported by statistics, mathematics, and computer science, aiming to cultivate urgently needed high-level interdisciplinary talents with big data processing and analytical capabilities.

The Applied Statistics Master's program currently has 10 faculty supervisors, including three professors and seven associate professors, 8 of whom hold doctoral degrees. Twelve part-time industry-expert adjunct supervisors are also engaged.

The discipline has established six internship bases through university-college collaborations, strengthening talent exchanges with government departments, enterprises, and financial institutions. It conducts extensive international collaborations and has co-organized multiple important domestic/international academic conferences. Faculty members have undertaken 10 provincial/ministerial-level research projects, received eight provincial/ministerial scientific awards, published over 100 high-quality papers, and authored nine textbooks/monographs.