Statistics is the science concerned with developing and studying methods for collecting, analyzing, interpreting and presenting empirical data. The MS and PhD degrees provide foundational training in the theoretical underpinnings of modern statistical methodologies as well as the application of those methodologies to real-world data science problems. Core training includes:
1. Probability and mathematical statistics;
2. Statistical methods most commonly used across a multitude of industries;
3. Statistical computing, specialized methodologies, and hands-on consulting
Individuals from a variety of backgrounds can make significant contributions to the field of statistics as long as they have sufficient background in statistics, mathematics, and computing.
Undergraduate preparation in statistics, mathematics, and computing should include multivariate calculus (the equivalent of UCI courses Mathematics 2A-B, 2D-E), linear algebra (121A), elementary analysis (140A-B), introductory probability and statistics (Statistics 120A-B-C), and basic computing (ICS 21).
For students with undergraduate majors outside of mathematics and statistics, it is possible to make up one or two missing courses during the first year in the program.
| 序号 | 课程介绍 | Curriculum |
| 1 | 中级概率论与统计理论 | Intermediate Probability and Statistical Theory |
| 2 | 统计方法I：线性模型 | Statistical Methods I: Linear Models |
| 3 | 统计方法II：分类数据 | Statistical Methods II: Categorical Data |
| 4 | 统计方法三：纵向数据 | Statistical Methods III: Longitudinal Data |
| 5 | 贝叶斯数据分析简介 | Introduction to Bayesian Data Analysis |
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