Applied Statistics

In the context of the strong development of information technology and the demand for data analysis across industries, the Master of Applied Statistics program in China is becoming an attractive choice for international students.

This major not only helps students master foundational knowledge of statistics but also provides practical application skills, especially in fields such as finance, big data, and scientific research.

Let's explore this major with StudyinChina.io!

Introduction to the Applied Statistics Major

The Master of Applied Statistics program is designed to meet the development of the statistics field, improve the talent training system in applied statistics, innovate training models, and enhance the quality of talent cultivation in this industry.

The program trains students with an international perspective in the field of statistics, helping them master core skills and apply statistical methods to solve practical problems, especially in areas such as finance, commerce, and business data mining.

Training Objectives

The training objectives of the Master of Applied Statistics for international students are:

• Equip students with basic knowledge of China's history, geography, society, and economy, as well as core socialist values and public ethical perspectives.
• Develop the ability to apply and expand statistical knowledge, skills, and methods in the practical environments of various countries, with a solid international vision.
• Ensure students can complete tasks in the field of statistics in Chinese, achieving the international Chinese proficiency standard of Level 5.
• Train high-level applied statistics professionals with good professional ethics and deep data analysis capabilities.

Who is Suitable for This Major?

The Applied Statistics major is suitable for those passionate about data, statistics, and analysis. Individuals who can work with numbers, enjoy analytical problems, optimization, and finding trends from large datasets are well-suited for this field. Ideal candidates may be:

• Graduates from majors such as computer science, mathematics, finance, economics, or social sciences requiring data analysis.
• Those wanting to enhance their knowledge in statistics and apply statistical methods to real-world problems in business or government.
• Individuals with a special interest in fields like finance, big data, machine learning, or market research.

As a major requiring logical thinking, problem-solving, and attention to detail, it is suitable for those with strong analytical skills and a love for tackling challenges with data.

Study Mode and Training Duration

• Study Duration: 2 years
• Study Mode: Full-time study, combining theoretical teaching with real-world case analysis, focusing on practical application training.

Core Courses of the Applied Statistics Major

Professional Internship

Students are required to participate in a professional internship for no less than six months, particularly in government organizations and enterprises where they can practice statistical work.

The internship aims to enhance the ability to apply theoretical knowledge to practice, solve problems in the work environment, and strengthen adaptability to social work.

Training Direction

The Master of Applied Statistics training program is built on the foundation of basic theoretical learning and professional knowledge, focusing on training practical application skills in statistics.

The training model combining "basic theory learning + professional learning + case and experimental teaching + practical internship" is the main training method.

Special emphasis is placed on developing the ability to analyze and solve practical problems, teamwork spirit, and communication skills.

Research Directions

1. Financial Statistics
2. Commercial Statistics
3. Business Data Mining

Degree

Upon completing the required credits and successfully defending their thesis, students who meet the degree requirements will be awarded a Master's degree in Applied Statistics.

Career Opportunities

• Data Analysis and Business Intelligence
  • Positions: Data Analyst, Business Intelligence Engineer
  • Skills: SQL/Python, Tableau/PowerBI
• Finance and Risk Management
  • Positions: Credit Scoring Model Specialist, Actuary
  • Techniques: GLM Models, Time Series Forecasting
• Medical and Biostatistics
  • Tools: SAS/R, CDISC Standard Datasets
  • Industries: CRO Companies, Pharmaceutical Companies
• New and Interdisciplinary Fields: Artificial Intelligence and Machine Learning
  • Positions: Algorithm Engineer
  • Required Knowledge: Statistical Learning Theory, TensorFlow/PyTorch
• Government and Public Policy
  • Positions: Big Data Analyst for Census, Socio-economic Index Modeling
  • Techniques: Survey Design, Policy Effectiveness Evaluation

Specialized Fields

• Quantitative Research (requires additional finance knowledge)
  • Competitive Advantage: Factor Mining, Backtesting System Development
  • Salary Reference: Citadel/Two Sigma
• Internet Data Science (requires technical ability)
  • Challenge: CTR Prediction for Recommendation Systems