统计软件

学分：3学分

先修课程：概率论与数理统计、线性代数

课程简介：

这门课介绍常用统计软件R的基本操作，包括数据分析和数据可视化。通过一个学期的学习，学生熟悉软件的使用环境和界面，懂得输入和输出不同的数据文件到R软件, 会探索数据和对数据进行基本的统计分析，包括回归分析和假设检验。通过学习基本的编程语言，学生可以做到灵活处理实际数据。该课程通过充足的例子来讲解软件如何操作。这门课程实践性强，学生需要多练习课本例子和做实际数据分析。

课程目标：

通过一个学期的学习，学生会做基本的数据整理，通过画图展现数据结构和特征；使用R对数据进行统计分析，包括回归分析和假设检验；深入思考构建统计模型的假设是否符合数据特征；对给定的数据，采用合适的数据分析方法；懂得对实际数据进行基本统计分析。

考核方式：

平时成绩（考勤、作业、分组讨论等）×30%+期末考试成绩×70%

课程教材：

William N Venables, David M Smith, An Introduction to R. 2009, ISBN:0964612086, ISBN13: 9780954612085.

Statistical Software

Credits: 3 Credits

Pre-requisite: Probability & Mathematical Statistics, Linear Algebra

Module Description：

This course introduces the basic operation of the widely used software R, with emphasis on data analysis and visualization. Throughout the semester, we will get familiar with the software environment, know how to input and output different data files into the software, and use the tools in the software to explore and analyze the data, including regression analysis and hypothesis testing. We will also teach some basic programming language of the statistical software, which enables the students to investigate the real data more freely. In the course, we will use various examples to illustrate the operations of the software. This course is interactive-learning based and students are required to try the examples by themselves.

Learning Outcome and Objectives：

By the end of the module, students should be able to: summarize and present data numerically and visually; use R to conduct the basic statistical inference, including simple linear regression, hypothesis testing; think critically about the data-based claims and the statistical model assumption; use the appropriate method for a given data; conduct basic statistical analysis for real data.

Assessment：

Assignments and Class Performance 30%, Final Exam 70%

Textbook and reference：

William N Venables, David M Smith, An Introduction to R. 2009, ISBN:0964612086, ISBN13: 9780954612085.