美国藤校康纳尔大学统计专业解析

康奈尔大学（cornell university），或称“康乃尔大学”，是由埃兹拉•康奈尔和安德鲁•迪克森•怀特于1865年所建立，是一所位于美国纽约州伊萨卡的私立研究型宗教信仰自由的大学，另有两所分校位于纽约市和卡塔尔大学城，为八个常春藤盟校中唯一一所在美国独立战争后创办的。与其它常青藤盟校大而全的发展策略不同，康奈尔一直致力于做“最好的本科教育”。康奈尔大学在伊萨卡总校区有七个本科生学院和七个研究生学院，每个学院都自主制订学术计划；学校在纽约市和卡塔尔大学城设有两处卫星医学院。目前康乃尔的校友逾240万名，先后有超过40位师生获颁诺贝尔奖。“台湾总统”李登辉、著名的桥梁专家茅以升，以及中国著名文学家和学者胡适都毕业于此校。

统计学是近几年的万金油专业，是应用数学的一个分支，主要通过利用概率论建立数学模型，收集所观察系统的数据，进行量化的分析、总结，并进而进行推断和预测，为相关决策提供依据和参考。统计学也被广泛应用在各学科之上，从自然科学到社会科学，再到人文科学，甚至是工商业及政府的情报决策之上，都会用到统计学。

康奈尔大学统计专业有2个学位项目：
1.mps：master of professional stuies in applie statistics--1-2年制项目，偏实践方向-，做一个大型的毕业项目进行毕业。
2.ms： master of science-2年制偏科研研究-项目方向毕业后继续申请ph博士项目，论文毕业。the ph program is intene to prepare stuents for a career in research an teaching at the university level or in equivalent positions in inustry or government. 博士项目对应的就业方向是进入到研究所或者政府机构进行科研研究工作或者进入到大学教学当老师。
专业设置
应用统计学 applie statistics
生物统计学 biometry
决策理论 ecision theory
计量经济学 econometrics
工程统计学 engineering statistics
实验设计 experimental esign
数理统计学 mathematical statistics
概率 probability
采样 sampling
社会统计学 social statistics
统计计算 statistical computing
随机处理
the mps program has two options:有2个分支方向，统计分析和数据科学
1.option i focuses on techniques of statistical analysis.
2.option ii, ata science, which along with statistical techniques puts more emphasis on computer science than option i, for example, high performance computing, atabases, mileware, an scripting.数据科学分支与统计分析分支相比，更侧重于计算机科学，比如高性能计算、数据库等等。
硕士课程相关：
both options require a total of at least 30 creit hours in require courses an electives. the 30 require creit hours must be earne while an mps stuent is enrolle in the mps program.
core require courses
stsci 5030: linear moels with matrices ﹙4 creits﹚
stsci 5080: probability moels an inference ﹙4 creits﹚
stsci 5953: mps professional evelopment ﹙1 creit﹚
stsci 5999: applie statistics mps ata analysis project ﹙4 creits﹚
aitional require courses for option ii
stsci 4060: python programming an its applications in statistics ﹙3 creits﹚
stsci 5060: atabase management an sas high performance computing with bms ﹙4 creits﹚
stsci 5065: big ata management an analysis ﹙3 creits﹚
statistical science electives
option i stuents must take at least 12 creit hours an option ii stuents at least 4 creits of statistical science electives from this list. option ii stuents cannot use stsci 4060, 5060, or 5065 as a statistical science elective since these courses are require as core option ii courses. 
stsci 3100: statistical sampling ﹙4 creits﹚
stsci 4520: statistical computing ﹙4 creits﹚
stsci 4060: python programming an its applications in statistics ﹙3 creits﹚
stsci 4100: multivariate analysis ﹙4 creits﹚
stsci 4110: categorical ata ﹙4 creits﹚
stsci 4140: applie esign ﹙4 creits﹚
stsci 4270: survival analysis ﹙3 creits﹚
stsci 4550: applie time series analysis ﹙4 creits﹚
stsci 4630: operations research tools for financial engineering ﹙3 creits﹚
stsci 4740: ata mining an machine learning ﹙4 creits﹚
stsci 4780: bayesian ata analysis: principles an practice
stsci 5640: statistics for financial engineering ﹙4 creits﹚
stsci 5010: applie statistical computation with sas ﹙4 creits﹚
stsci 5060: atabase management an sas high performance computing with bms ﹙4 creits﹚
stsci 5065: big ata management an analysis ﹙3 creits﹚
stsci 6070: functional ata analysis ﹙3 creits﹚
stsci 6520: computationally intensive statistical methos ﹙4 creits﹚
other approve mps electives
aem 7100: econometrics i ﹙3 creits﹚
btry 3090: theory of interest ﹙3 creits﹚
btry 4830: quantitative genomics an genetics ﹙4 creits﹚
btry 4840: computational genetics an genomics ﹙4 creits﹚
btry 6381: bioinformatics programming ﹙3 creits﹚
cs 4780: machine learning ﹙4 creits﹚
cs 5786: machine learning for ata science ﹙4 creits﹚
math 4740: stochastic processes ﹙4 creits﹚
orie 3120: practical tools for operations research, machine learning, an ata science ﹙4 creits﹚
orie 4630: operations research tools for financial engineering ﹙3 creits﹚
orie 4741: learning with big messy ata ﹙4 creits﹚
orie 5510: introuction to engineering stochastic processes i ﹙4 creits﹚
orie 5580: simulation moeling & analysis ﹙4 creits﹚
orie 5581: monte carlo simulation ﹙2 creits﹚
orie 5600: financial engineering with stochastic calculus i ﹙4 creits﹚
orie 5610: financial engineering with stochastic calculus ii ﹙4 creits﹚
orie 5640: statistics for financial engineering ﹙4 creits﹚
orie 6500: applie stochastic processes ﹙4 creits﹚
orie 6741: bayesian machine learning ﹙3 creits﹚
orie 6780: bayesian statistics an ata analysis ﹙3 creits﹚

想要了解康奈尔大学硕士申请具体要求，请联系王老师吧。