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回复 10# neversmomo
在这里。。。有三个方向的,其中bio的应该最好吧休斯顿有全美最大的cancer研究中心,听说bio的很多学生都去那工作。。
Overview of the M.Stat Program
The Professional Master in Statistics (M.Stat) Program offers a customized and individualized programs based on the interests and career objectives of the student. Students are allowed to choose either a broad-based or specialized program of study. All choices, however, provide a balanced training in statistical methods, computational statistics, and statistical theory, and are intended to prepare the student to adapt statistical methodologies to practical problems in a professional setting.
Course of Study
The M.Stat is a non-thesis Master's degree, and does not require an internship. Students are required to take 30 hours of approved coursework, with additional recommended career-enhancing enrichment courses. Depending on the student's selected specialization, the mix of required, track-specific and elective courses will be jointly determined by the student and the graduate advisor. You will meet with your advisor during the first year of the program to select an individualized plan of study, with periodic tune-ups as the program progresses.
The program normally takes three semesters of full-time course work, although very strong students may finish in two semesters; it is also possible to complete the program on a part-time basis, so long as the student eventually satisfies the 1-semester residency requirement.
Core Curriculum
Required Courses
These courses are normally completed by the end of the first 2 semesters
# Overview of Mathematical Statistics (STAT 431). Χ
# Statistical Computing and Graphics (STAT 405)
# Introduction to Regression and Statistical Computing (STAT 410)
# Advanced Statistical Methods (STAT 411)
Courses Specific to Area of Specialization
These courses are recommended for the specialization track that is to be developed between the M.Stat student and their advisor (Director of M.Stat Program). Courses include recommended core and elective courses. The current recommended core courses are listed below; recommended electives and courses for certain tracks such as Applied Statistics for Industry and Preparation for Ph.D. Studies are developed separately.
Financial Statistics and the Statistics of Risk
# Computational Finance I - Market Models (STAT 686)
# Comp Finance II - Applied Time Series and Forecasting (STAT 621)
# Quantitative Financial Analytics (STAT 682)
. From 1point 3acres bbs
Bioinformatics, Statistical Genetics, and Biostatistics
# From Sequence to Structure: An Introduction to Computational Biology (STAT 470)
# Biostatistics (STAT 553)
# Probability in Bioinformatics and Genetics (STAT 623)
# Probability and Statistics for Systems Biology (STAT 673)
Statistical Computing and Data Mining
# Bayesian Data Analysis (STAT 622)
# Multivariate Analysis (STAT 541)
# Simulation (STAT 542)
# Data Mining and Statistical Learning (STAT 640)
Environmental Statistics
# Quantitative Environmental Decision Making (STAT 685)
# Environmental Risk Assessment & Human Health (STAT 684)
Free Electives
Electives are targeted in the subfield of interest. Students may be asked to take specific courses outside the department, depending on the incoming background of the student, career objectives and funding sources. |
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