北卡州立 NCSU统计学硕士+ 查看更多
北卡州立 NCSU
统计学硕士
+ 查看更多
学生可以从多个专业中进行选择。除了传统的(无专业)统计学硕士学位外,还有四个分支方向可供选择:
- Traditional: 传统学位的目标是在统计学的核心领域打下坚实的基础,例如实验设计和计算统计。这条路线可能为在跨学科团队中工作的人提供最好的准备
- Biostatistics: 生物统计学专业将提供统计方法方面的培训,这些方法可用于医学研究、制药行业和公共卫生领域进行的研究的设计和分析。学生将学习临床试验和流行病学研究的基础知识,并将了解用于分析事件发生时间、分类和纵向数据的统计方法的最新进展
- Environmental Statistics: 环境统计专业的学生应该参与环境领域的研究和咨询,并与环境科学家互动。这可以通过部门或大学的项目或通过在环境保护局和三角研究园的国家统计科学研究所实习来完成
- Statistical Genetics: 统计遗传学专业适合那些对遗传数据与基因组科学、医学和农业等领域的相关性感兴趣的人
- Financial Concentration: 金融专业通过与金融数据的分析、解释和理解相关的选修课补充统计核心课程
项目时长:一年全日制 (全日制)
项目授课地点:美国 北卡罗莱纳 罗利市
申请要求
申请流程:
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必修课程:
ST 501 — Fundamentals of Statistical Inference I
First of a two-semester sequence in probability and statistics taught at a calculus-based level.
First of a two-semester sequence in probability and statistics taught at a calculus-based level.
ST 502 — Fundamentals of Statistical Inference II
Second of a two-semester sequence in probability and statistics taught at a calculus-based level.
Second of a two-semester sequence in probability and statistics taught at a calculus-based level.
ST 503 — Fundamentals of Linear Models and Regression
Estimation and testing in full and non-full rank linear models.
Estimation and testing in full and non-full rank linear models.
ST 517 — Applied Statistical Methods I
Course covers basic methods for summarizing and describing data, accounting for variability in data, and techniques for inference.
Course covers basic methods for summarizing and describing data, accounting for variability in data, and techniques for inference.
ST 518 — Applied Statistical Methods II
Courses cover simple and multiple regression, one- and two-factor ANOVA, blocked and split-plot designs. Data with multiple sources of error such as longitudinal data collected over time and categorical data analysis including regression with binary response will also be covered.
Courses cover simple and multiple regression, one- and two-factor ANOVA, blocked and split-plot designs. Data with multiple sources of error such as longitudinal data collected over time and categorical data analysis including regression with binary response will also be covered.
ST 542 — Statistical Practice
This course will provide a discussion-based introduction to statistical practice geared towards students in the final semester of their Master of Statistics degree.
This course will provide a discussion-based introduction to statistical practice geared towards students in the final semester of their Master of Statistics degree.
ST 555 — Statistical Programming I
An introduction to programming and data management using SAS, the industry standard for statistical practice.
An introduction to programming and data management using SAS, the industry standard for statistical practice.
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