统计学

学分：6

统计学是致力于研究不确定性的一门学科，出现在我们生活的方方面面。我还能活多久？伯明翰城市足球队获得本赛季英格兰足总杯的概率是多少？今天会下雨吗？我本周中彩票的概率是多少？统计学理论和方法是我们理解此类不确定性问题的基础，也是一项日益受追捧的技能。例如，谷歌使用统计学方法改进其搜索算法；医学研究活动使用统计学方法设计并分析临床试验，评估新型癌症疗法是否有效；精算和经济团队使用统计学方法对未来的风险和收益做出精确的预测。

本课程在概率与统计学的介绍性资料的基础上，将同时详述各种统计理论和方法。相关问题包括经典线性模型（同时简述方差分析）、处理离散数据的基本方法、继续学习概率分布理论及估计与假设检验测验理论的某些知识。在计算课程中，本课程将利用统计软件包讲述统计方法在部分经典数据集合分析中的应用。

在本课程结课时，学生应能够：

•说明对统计推断原则的基本理解

•可解答分布式微积分领域的简单问题

•可确认统计模型应用的标准情景

•可构建统计模型，并通过该模型分析数据

•展示使用标准统计软件包的流畅程度

Statistics 统计学

Credits: 6

Statistics is the study of uncertainty, which arises in all aspects of life. How long will I live for? What is the probability that Birmingham City will win the FA Cup this season? Will it rain today? What is the probability that I will win the lottery this week? Statistical theory and methods are fundamental to our understanding of such uncertainty, and are an increasingly sought after skill. For example, Google uses statistics to improve their search algorithms; medical research uses statistics to design and analyse clinical trials evaluating whether a new cancer treatment is effective; and actuarial and economic teams use statistics to make accurate predictions about future risks and outcomes.

This module presents a parallel development of statistical theory and methods, building on the introductory material in Probability & Statistics. Topics covered include classical linear models, with an introduction to the analysis of variance; basic methods for handling discrete data; further work in the theory of probability distributions; and some aspects of the theory of estimation and hypothesis testing. In the computing sessions, a statistical package is used to illustrate the application of statistical methods to the analysis of some typical data sets.

By the end of this module, students should be able to:

•demonstrate a basic understanding of the principles of statistical inference;

•be able to handle simple problems in the distributional calculus;

•be able to identify standard situations to which statistical models apply;

•be able to build statistical models and use them for the analysis of data;

•demonstrate fluency with a standard statistical package.