爱荷华大学生物统计学硕士课程要求

爱荷华大学生物统计学硕士课程要求

生物统计学理学硕士课程要求至少38学时的研究生学分。学生必须保持至少3.00的gpa。那些在7个小时的课程中获得C级成绩的人可能会被开除该课程。

该计划提供有关实验设计以及与生物医学或公共卫生问题相关的数据分析的培训。它强调处理定量信息的数学，统计和计算机方法，并为学生提供了获得有关各种问题的统计咨询经验的机会。

硕士生需要在部门教员的指导下完成深入的指导，并进行最终的综合式考试。

拥有生物统计学专业的理科硕士需要以下课程。

1、核心课程：

BIOS:5510：Biostatistical Computing (taken twice for 2 s.h. each; topics should be programming with R and programming with SAS)：4

BIOS:5710 & BIOS:5720 Biostatistical Methods I-II：8

BIOS:5730 Biostatistical Methods in Categorical Data：3

BIOS:6610 Statistical Methods in Clinical Trials：3

BIOS:7500 Preceptorship in Biostatistics：3

EPID:4400 Epidemiology I: Principles：3

One of these sequences:

STAT:4100-STAT:4101 Mathematical Statistics I-II：6

STAT:5100-STAT:5101 Statistical Inference I-II (required for students who intend to earn a Ph.D.)：6

Public Health Requirement

CPH:6100 Essentials of Public Health：2

Responsible Conduct of Research Training

This course:

BIOS:7270 Scholarly Integrity in Biostatistics：

1

2、选修课：

学生至少要完成5-6学时的选修课，并且至少要完成3学时的定量课程(统计或生物统计学)。建议学生将生物学/公共卫生课程作为另一门选修课，特别是对于那些以前没有接触过这些领域的人。选修课必须由顾问和研究生课程主任批准。

IOS:6210 Applied Survival Analysis：3

BIOS:6310/STAT:6550 Introductory Longitudinal Data Analysis：3

BIOS:6420 Survey Design and Analysis：3

BIOS:6650 Causal Inference：3

BIOS:6720 Statistical Machine Learning for Biomedical and Public Health Data：3

BIOS:6810 Bayesian Methods and Design：3

BIOS:7110 Likelihood Theory and Extensions：4

BIOS:7120：Advanced Topics in Biostatistics：4

BIOS:7210/STAT:7570 Survival Data Analysis：3

BIOS:7230 Advanced Clinical Trials：3

BIOS:7240 High-Dimensional Data Analysis：3

BIOS:7250 Theory of Linear and Generalized Linear Models：4

BIOS:7310 Longitudinal Data Analysis：3

BIOS:7330 Advanced Biostatistical Computing：3

BIOS:7410/STAT:7510 Analysis of Categorical Data：3

BIOS:7600 Advanced Biostatistics Seminar (topics include statistical methods in bioinformatics, model selection, spatial modeling, statistical analysis of network data：3

BIOS:7700 Problems/Special Topics in Biostatistics：

1

BIOL:4213 Bioinformatics：4

CBH:4105 Introduction to Health Promotion and Disease Prevention：3

CPH:5100 Introduction to Public Health：3

CS:5110 Introduction to Informatics：3

ECE:5220 Computational Genomics：3

GENE:7191 Human Molecular Genetics：3

HMP:4000 Introduction to the U.S. Health Care System：3

ISE:4172 Big Data Analytics：3

OEH:4240 Global Environmental Health：3

PATH:5270 Pathogenesis of Major Human Diseases：3

PATH:8133 Introduction to Human Pathology for Graduate Students：4

STAT:4520 Bayesian Statistics：3

STAT:6540 Applied Multivariate Analysis：3

STAT:6560 Applied Time Series Analysis：3

STAT:7200 Linear Models：4

STAT:7400 Computer Intensive Statistics：3

STAT:7520 Bayesian Analysis：3