Biostatistics: A Second Statistics Course Preparing Undergraduates for Research

数学（21）该项目在Sweet Briar学院（一所女子文科学院）开设了一门新的生物统计学课程，以支持新设立的将数学和生物学纳入本科课程的倡议。它完成了统计学和生物数学两个新的未成年人的课程。该项目的智力价值在于课程的改进，使广泛使用的统计方法提供给学生在他们的教育早期，使用现代，计算密集型技术，并强调数据和理论的概念，使学生将学习统计思维在一个生动有趣的方式。在解决学生的需求，众所周知，本科生比以往任何时候都有更多的机会做研究。事实上，研究经验是许多研究生课程的入学期望。当学生阅读研究文献，计划实验和分析数据时，他们需要了解超出入门统计课程范围的统计概念和方法。对于计划攻读生命科学和医学研究生的学生来说，生物统计学是宝贵的准备。然而，文理学院很少有资源提供超过一般的入门统计课程。改编的材料包括国家科学基金会资助的项目“超越传统统计方法”（NSF-9751644）中关于自助估计和逻辑回归的模块。这些都是计算密集型的统计方法，已被广泛采用的科学和工程研究，但尚未成为普遍的本科统计课程。本课程采用积极的学习，通过实验室练习，项目，小组解决问题和讨论，并根据课堂上产生的数据演示。活动改编自教学统计：一袋技巧和统计教学和资源库。更广泛的影响。生物统计学的新课程为其他文科院校提供了榜样。它建立在已经在甜石楠学院正在进行的课程改革的基础上，是生物数学和统计学两个新的未成年人课程的必修课。该课程是目前由Sweet Briar学院和弗吉尼亚大学医学院生物数学技术中心开发的生物数学更大计划的一个组成部分。课程大纲，材料和活动都张贴在课程网站上，供其他机构的教师访问。

Mathematics(21) This project develops a new Biostatistics course at Sweet Briar College, a liberal arts college for women, to support a newly established initiative for integrating mathematics and biology in the undergraduate curriculum. It completes the curriculum for two new minors in Statistics and Biomathematics.Intellectual merit. The project's intellectual merit lies in curriculum improvements that make widely used statistical methods available to students earlier in their education, that use modern, computing-intensive techniques, and that emphasize data and concepts over theory so that students will learn statistical thinking in a lively and interesting way. In addressing the needs of students it is known that undergraduates have more opportunities than ever to do research. In fact, research experience is an expectation for admission in many graduate programs. As students read research literature, plan experiments, and analyze data, they need to understand concepts and methods of statistics that lie beyond the scope of an introductory statistics course. Biostatistics is valuable preparation for students who plan to do graduate study in life sciences and medicine. However, liberal arts colleges seldom have the resources to offer more than a general introductory statistics course. Materials adapted include modules from the NSF-funded project "Beyond Traditional Statistical Methods" (NSF-9751644) on bootstrap estimates and logistic regression. These are computing-intensive statistical methods that have been widely adopted in scientific and engineering research but have not yet become common in the undergraduate statistics curriculum.The course employs active learning through lab exercises, projects, group problem solving and discussion, and demonstrations based on data generated in class. Activities adapted from Teaching Statistics: A Bag of Tricks and the Statistics Teaching and Resource Library. Broader impact. The new course in Biostatistics serves as a model for other liberal arts institutions. It builds on curriculum changes that are already in progress at Sweet Briar College and is a required course for two new minor programs in Biomathematics and in Statistics. The course is a component of a larger program in biomathematics currently being developed by Sweet Briar College and the Center for Bio-mathematical Technology at the University of Virginia Medical School. The course outline, materials, and activities are posted on a course website for access by faculty members at other institutions.