15.075 2003秋季课程：应用统计(Applied Statistics, Spring 2003)
|
图示机率与统计的区别。（图片由麻省理工开放式课程提供，改编自Gilbert, Norma 着《统计学》，W.B. Saunders Co.， 1976）
Diagram showing the difference between statistics and probability. (Image by MIT OpenCourseWare. Based on Gilbert, Norma. Statistics. W.B. Saunders Co., 1976.)
Diagram showing the difference between statistics and probability. (Image by MIT OpenCourseWare. Based on Gilbert, Norma. Statistics. W.B. Saunders Co., 1976.)
课程重点
透过全面的课堂讲稿，读者可以了解15.075应用统计的内容。学生将透过作业以及课堂讲稿里的实例，亲身体验统计软件的操作。
Material in 15.075 is presented through its comprehensive set of lecture notes. Students receive hands-on experience with statistical software through the assignments and with examples in the lecture notes.
课程描述
这门课程是应用统计学以及数据分析的介绍。主题包含了数据收集与探索，基础推论，简单与多元线性回归 （simple and multiple linear regression），方差分析 （analysis of variance, ANOVA），非参数方法 （nonparametric methods） 以及统计计算（statistical computing）。这不是一门数理统计的课程；本课程兼顾统计理论及应用。必备先修科目为微积分、概率以及线性代数。
This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra.
This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra.
在此对于 Roy Welsch教授 （麻省理工学院），Gordon Kaufman教授 （麻省理工学院），Jacqueline Telford教授 （约翰霍普金斯大学Johns Hopkins University） 以及 Ramón León教授 （田纳西大学（University of Tennessee）） 在课程资料上的贡献表达感谢之意。
We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material.
