统计与数据科学

The 统计与数据科学 major is designed for students pursuing a career as a data scientist or statistician. It combines cutting-edge techniques in data science with mathematically rigorous statistics. Statistics courses in the curriculum are project-driven with an emphasis on the analysis of real-world data using statistical methods implemented by powerful statistical software. This program prepares students for a career in business or industry utilizing statistics or data science but is also sufficiently rigorous to prepare a student for graduate work in a related field.

The digital revolution has created vast quantities of data. Extracting knowledge and insight from this avalanche of information is the goal of data science, a rapidly growing field with applications in such areas as marketing, 教育, 和体育, as well as scientific fields such as genomics, 神经科学, 粒子物理.

职业发展机会

Decision-makers have access to more data than ever before, but deriving meaning and actionable insights from that data requires specialized tools and expertise. For that reason, graduates with degrees in statistics and data science are in high demand.

Currently, there is a global data scientist shortage. It is estimated that within the next two years, there will be twice as many data science jobs as there will be people to fill those roles. This means extensive job opportunities for individuals with the necessary 教育 and skills.

课程

UE's program in statistics and data science combines state-of-the-art tools and techniques from the field of data science with a mathematically rigorous tradition of classical applied statistics. 这个项目的学生将……

  • Engage through project-driven courses. Data analysis projects offered throughout the curriculum expose students to the entire work cycle of predictive modeling, including problem formulation, acquisition and cleaning of data, 模型选择与拟合, 解释, 和报告.
  • Master cutting-edge statistical software. Students gain fluency in the statistical software currently in use within business and industry, 包括R, Python, 和BigQuery.
  • Receive a first-class liberal arts 教育. Working with “big data” requires more than quantitative and technological skills—it also requires an ability to frame questions, to bring diverse teams together, to make ethical and informed decisions, and to communicate results to decision-makers. A UE 教育 provides students with broad foundational knowledge in the arts and sciences, as well as the critical thinking and communication skills that employers value.

Details on program requirements and course descriptions can also be found in the 目录.

额外的信息

Sample 4-year Plan Beginning in an Odd Year

与Harlaxton

Sample 4-year Plan Beginning in an Odd Year with Harlaxton
秋天 春天
大一新生 数学221 -微积分I
统计166 – Intro to R for Data Science
数学222 -微积分II
统计266 – Introductory Statistics with R
二年级学生 CS 210 ——基金. 程序设计I
统计267 -实验设计
数学365 ——概率
数学341 -线性代数
数学466 ——统计
CS 215 ——基金. 程序设计学II
初级 统计361 -线性模型 Harlaxton
高级 统计300 -现实世界中的数据分析
统计474 – Techniques for Large Data Sets
统计362 -机器学习
统计493 -统计建模

没有Harlaxton

Sample 4-year Plan Beginning in an Odd Year without Harlaxton
秋天 春天
大一新生 数学221 -微积分I
统计166 – Intro to R for Data Science
数学222 -微积分II
统计266 – Introductory Statistics with R
CS 210 ——基金. 程序设计I
二年级学生 统计267 -实验设计
数学365 ——概率
CS 215 ——基金. 程序设计学II
数学341 -线性代数
数学466 ——统计
初级 统计361 -线性模型 统计362 -机器学习
高级 统计300 -现实世界中的数据分析
统计474 – Techniques for Large Data Sets
统计493 -统计建模

Sample 4-year Plan Beginning in an Even Year

与Harlaxton

Sample 4-year Plan Beginning in an Even Year with Harlaxton
秋天 春天
大一新生 数学221 -微积分I
统计166 – Intro to R for Data Science
数学222 -微积分II
统计266 – Introductory Statistics with R
CS 210 ——基金. 程序设计I
二年级学生 统计267 -实验设计
数学365 ——概率
CS 215 ——基金. 程序设计学II
数学341 -线性代数
数学466 ——统计
初级 统计361 -线性模型
统计474 – Techniques for Large Data Sets
Harlaxton
高级 统计300 -现实世界中的数据分析 统计362 -机器学习
统计493
-统计建模

没有Harlaxton

Sample 4-year Plan Beginning in an Even Year without Harlaxton
秋天 春天
大一新生 数学221 -微积分I
统计166 – Intro to R for Data Science
数学222 -微积分II
统计266 – Introductory Statistics with R
CS 210 ——基金. 程序设计I
二年级学生 统计267 -实验设计
数学365 ——概率
CS 215 ——基金. 程序设计学II
数学341 -线性代数
数学466 ——统计
初级 统计361 -线性模型
统计474 – Techniques for Large Data Sets
统计300 -现实世界中的数据分析
统计362
-机器学习
高级 统计300 -现实世界中的数据分析
统计493 -统计建模

Note: CS 215* can be replaced by a computer-based course. Harlaxton: 统计361 can be taking in the fall of the senior year.

STAT课程设置
统计课程 频率
统计166 – Intro to R for Data Science 每年秋季
统计266 - Introductory Statistics with R 每年春天
统计267 - Experimental Design 每年秋季
统计300 - Data Analysis in Real World 每年秋季
统计361 -线性模型 每年秋季
统计362 -机器学习 每年春天
统计474 - Techniques for Large Data Sets 每一次均匀的坠落
统计493 - Statistical Modeling 每年春天
数学和计算机科学课程
数学与计算机科学课程 频率
数学221,222 -微积分 秋天,春天和夏天
数学365 -概率 每年秋季
数学466 - Mathematical Statistics 每年春天
数学341 -线性代数 每年春天
CS 210, 215 - 介绍 to Programming 每年秋天和春天

数学 课程的依赖 Chart