德克薩斯大學奧斯汀分校統(tǒng)計與數(shù)據(jù)科學

指南者留學 2022-04-19 03:19:10

UT-Austin的全稱是University of Texas at Austin的Statistics & Data Sciences,即德克薩斯大學奧斯汀分校統(tǒng)計與數(shù)據(jù)科學,下面將詳細介紹UT-Austin的的項目特點/院系介紹、UT-Austin的的研究生申請要求。

UT-Austin的「德克薩斯大學奧斯汀分校統(tǒng)計與數(shù)據(jù)科學」

德克薩斯大學奧斯汀分校

UT-Austin的培養(yǎng)計劃

The Master's in Statistics degree at The University of Texas at Austin is administered through the Deparment of Statistics and Data Sciences, but has its own graduate advisor and graduate studies committee. The Graduate Studies Committee for this program consists of faculty members from a variety of departments across campus. The focus of the program is a mix of theory and application.
The program is offered in two tracks: track A and track B. Track A is designed for students seeking a terminal MS Statistics degree or for students currently pursuing doctoral programs other than statistics. Track B is designed for students enrolled in the PhD Statistics program who transfer into the MS Statistics program from the PhD Statistics program. Both tracks require completion of thirty-two semester hours of approved coursework and include the completion of a master’s report.

UT-Austin的研究領(lǐng)域(英文版)

1、 Statistical Methods I

2、Statistical Methods II

3、Mathematical Methods for Statistical Analysis

4、Introduction to Probability and Statistics

5、Data Analysis Applications

6、Statistical Modeling I

7、Statistical Modeling II

8、Topics in Statistics and Probability

9、Topics in Applied Statistics

10、 Linear Models

11、Time Series and Dynamic Models

12、Data Mining

13、Computational Economics

14、Numerical Analysis: Linear Algebra

UT-Austin的研究領(lǐng)域(中文版)

1、統(tǒng)計方法1

2、統(tǒng)計方法2

3、數(shù)學方法進行統(tǒng)計分析

4、概率和統(tǒng)計介紹

5、數(shù)據(jù)分析應(yīng)用

6、統(tǒng)計建模1

7、統(tǒng)計建模2

8、概率和統(tǒng)計主題

9、應(yīng)用統(tǒng)計主題

10、線性模型

11、時間序列模型和動態(tài)模型

12、數(shù)據(jù)挖掘

13、計算經(jīng)濟學

14、數(shù)值分析:線性代數(shù)

UT-Austin的申請要求

托福79或雅思6.5,GRE閱讀均分160數(shù)學均分164寫作3.7,GPA均分3.50,學費$23,304/年,申請截止日期12月15日

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德克薩斯大學奧斯汀分校 統(tǒng)計與數(shù)據(jù)科學 
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