康奈尔大学的立校之本是任何人都有获得教育的平等权利，是常春藤盟校中第一所实行性别平等的男女合校大学，在招生录取上最早实行不计贵族身份，不分信仰和种族，并以创建学科齐全、包罗万象的新型综合性大学为建校宗旨，因而该校被誉为美国历史上第一所具有真正意义的全民大学。
康奈尔大学研究生院共8个学院与一个继续教育与暑期课程培训（continuing eucation an summer sessions）。其中，包括一个研究生院以及7个专业学院。专业学院分别是兽医学院、康奈尔法学院、约翰逊商学院、康奈尔医学院、康奈尔多哈医学院、康奈尔医学研究学院、康奈尔大学技术学院、继续教育与暑期课程培训。康奈尔大学研究生院主要是针对近100个学术专业领域提供的学术及专业学位，下设有多个独立学院及研究中心。具体分为查理斯·戴森应用经济与管理学院、应用与工程物理学院、康奈尔大学考古与材料研究学院、应用数学中心、化学与生物分子工程学院、土木与环境工程学院、电气与计算机工程学院、人类生态学院、酒店管理学院、产业与劳动关系学院、运筹与信息工程学院、康奈尔大学公共事务学院。
今天我们一起来看一下康奈尔大学的统计专业的详细介绍：
The master of professional stuies ﹙m.p.s.﹚ egree in applie statistics is for persons intereste in professional careers in business, inustry or government. the m.p.s. program has three main components:
A two-semester core course covering a wie range of statistical applications, computing, an consulting
An in-epth statistical analysis project
Elective coursework rawn from the resources of the epartment of statistical science.
The program can be complete in one year by a well-prepare stuent with the equivalent of an unergrauate egree in statistics or applie mathematics. stuents with less preparation can make up any missing prerequisites while at cornell; in this case the program will take one to two years to complete.
The m.p.s. is intene for persons who want a short-term ﹙one year﹚ master＇s egree so as to go into business, inustry, or government statistical work. the m.p.s. is not equivalent to an m.s. on several counts: the m.p.s. has a project ﹙a large-scale>
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﹚
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