考研留学两不误，成功拿到华威大学的offer-新东方前途出国

　　华威大学（全球QS排名61）  

　　             --------上海交通大学（全球QS排名50） 

　　Mathematical Finance 数学金融 

　　学制：一年 

　　学费： 31000英镑 

　　雅思要求： 总分7分，两门6分或者6.5分，两门7分 

　　课程设置：  

　　Core modules 核心课程 

　　Programming for Quantitative Finance 量化金融编程 

　　Stochastic Calculus for Finance 金融随机微积分 

　　Financial Statistics 财务统计 

　　Simulation and Machine Learning for Finance 金融模拟和机器学习 

　　Asset Pricing and Risk 资产定价和风险 

　　Financial Econometrics 金融计量经济学 

　　Applications of Stochastic Calculus in Finance 随机微积分在金融中的应用 

　　Dissertation 论文 

　　Optional modules选修课程 

　　Optional modules can vary from year to year. Example optional modules may include: 

　　Advanced Risk Management 高级风险管理 

　　Statistical Learning and Big Data 统计学习和大数据 

　　Behavioural Finance 行为金融 

　　Brownian Motion 布朗运动 

　　Advanced Trading Strategies 高级交易策略 

　　Partial Differential Equations in Finance 金融中的偏微分方程  

　　推荐专业二： Statistics (MSc)统计学 

　　学制：一年 

　　学费： 29950英镑 

　　雅思要求： 总分6.5分，单科不低于6分 

　　课程设置：  

　　Core modules 核心课程 

　　Statistical Methods 统计方法 

　　The module content will include a thorough grounding in classical and Bayesian methods of statistical inference with an introduction to selected modern developments in statistical methodology. Since MSc students have different background knowledge in statistics, we start afresh although a solid mathematical background is assumed. At the end of the course you will have a solid background in basic concepts of statistical methodology and knowledge at an advanced level in some areas. 该模块的内容将包括对经典和贝叶斯统计推断方法的全面基础，并介绍统计方法学的选定现代发展。由于理学硕士学生在统计学方面具有不同的背景知识，因此尽管假定具有扎实的数学背景，我们还是重新开始。在课程结束时，您将在统计方法的基本概念和某些领域的高级知识方面拥有扎实的背景。 

　　An Introduction to Statistical Practice 统计实践导论 

　　Introduction to Statistical Practice module introduces statistical computing, using R, through hands-on practical classes on the analysis of real data from a variety of scientific and other disciplines; and develops such skills are report-writing, statistical graphics, etc. 统计实践介绍模块通过对来自各种科学和其他学科的真实数据进行分析的动手实践课程，介绍使用 R 的统计计算；并培养这样的技能是报告写作、统计图表等。 

　　Dissertation 论文 

　　To complete the MSc, a student also undertakes a substantial project under the supervision of a Department member, and writes a dissertation reporting the results. Such projects can be in any of the areas covered by the MSc, including applied statistics, statistical methodology, computational methods, probability etc. 为了完成理学硕士课程，学生还需要在系成员的监督下进行一个实质性的项目，并撰写论文报告结果。这些项目可以是理学硕士所涵盖的任何领域，包括应用统计学、统计方法、计算方法、概率等。 

　　Optional modules 选修课程 

　　The remaining six modules are chosen from a wide range of options, subject to availability, to suit the interests of individual students. The options include: 其余六个模块从广泛的选项中选择，视情况而定，以满足个别学生的兴趣。选项包括： 

　　Advanced Topics in Data Science  数据科学高级主题 

　　This module will be comprised of three selected topics in the area of computational challenges associated with data analysis. The topics may change year to year. Some examples of topics from previous academic years: Deep Learning for Natural Language Processing, Decision Trees and Random Forests, Model Comparison and Selection, Artificial Neural Networks, Introduction to Reinforcement Learning and Modelling the Written Word: Compression and Human-Computer-Interfaces. 该模块将由与数据分析相关的计算挑战领域的三个选定主题组成。主题可能会逐年变化。前学年主题的一些示例：自然语言处理的深度学习、决策树和随机森林、模型比较和选择、人工神经网络、强化学习简介和文字建模：压缩和人机界面。 

　　Bayesian Forecasting and Intervention with Advanced Topics 高级主题的贝叶斯预测和干预 

　　Forecasting is a vital prerequisite to decision making. This course offers a very powerful fundamental probabilistic approach to forecasting, controlling and learning about uncertain commercial, financial, economic, production, environmental and medical dynamic systems. The theory will be illustrated by real examples from industry, marketing, finance, government, agriculture etc. A familiarity with the material in this module will be very useful to all students planning a career involving a component of industrial, business or government statistics. 预测是决策的重要先决条件。本课程提供了一种非常强大的基本概率方法来预测、控制和学习不确定的商业、金融、经济、生产、环境和医学动态系统。该理论将通过来自工业、市场营销、金融、政府、农业等的真实例子来说明。熟悉本模块中的材料对于所有计划从事工业、商业或政府统计组成部分的职业的学生都非常有用。 

　　Applied Stochastic Processes with Advanced Topics 高级主题的应用随机过程 

　　This module provides an introduction to concepts and techniques which are fundamental in modern applied probability theory and operations research: Models for queues, point processes, and epidemics. Furthermore, we study notions of equilibrium, threshold behaviour, and description of structure. The ideas presented in this module have a vast range of applications, for example routing algorithms in telecommunications (queues), assessment of apparent spatial order in astronomical data (stochastic geometry), description of outbreaks of disease (epidemics). 该模块介绍了现代应用概率论和运筹学中的基本概念和技术：队列模型、点过程模型和流行病模型。此外，我们研究平衡的概念、阈值行为和结构描述。本模块中提出的想法具有广泛的应用，例如电信（队列）中的路由算法、天文数据中表观空间顺序的评估（随机几何）、疾病爆发的描述（流行病）。 

　　Medical Statistics with Advanced Topics 具有高级主题的医学统计 

　　Modern applications of statistics to medicine are highly developed, and many medical research papers employ statistical techniques. Large numbers of statisticians are employed in medical research establishments, particularly in pharmaceutical companies and medical schools. Medical statistics continues to be a buoyant area for statistical recruitment. The course will explain why and how statistics is used in medicine, and study some of the statistical methods commonly used in medical research. We will include examples from our own research. The statistical techniques applied to medical data are also relevant in other applications. 统计学在医学上的现代应用得到了高度发展，许多医学研究论文都采用了统计技术。大量统计学家受雇于医学研究机构，尤其是制药公司和医学院。医学统计仍然是统计招聘的一个活跃领域。本课程将解释为什么以及如何在医学中使用统计，并学习一些医学研究中常用的统计方法。我们将包括我们自己研究中的例子。应用于医疗数据的统计技术也与其他应用相关。 

　　Monte Carlo Methods 蒙特卡罗方法 

　　When modelling real world phenomena statisticians are often confronted with the following dilemma: should we choose a standard model that is easy to compute with or use a more realistic model that is not amenable to analytic computations such as determining means and p-values. We are faced with such choice in a vast variety of application areas, some of which we will encounter in this module. These include financial models, genetics, polymer simulation, target tracking, statistical image analysis and missing data problems. With the advent of modern computer technology we are no longer restricted to standard models as we can use simulation-based inference. 在对现实世界的现象建模时，统计学家经常面临以下困境：我们应该选择易于计算的标准模型，还是使用更现实的模型，该模型不适用于确定均值和 p 值等分析计算。我们在各种各样的应用领域都面临着这样的选择，其中一些我们将在本模块中遇到。其中包括金融模型、遗传学、聚合物模拟、目标跟踪、统计图像分析和数据缺失问题。随着现代计算机技术的出现，我们不再局限于标准模型，因为我们可以使用基于模拟的推理。 

　　Designed Experiments with Advanced Topics 高级主题的设计实验 

　　Designed experiments are used in industry, agriculture, medicine and many other areas of activity to test hypotheses, to learn about processes and to predict future responses. The primary purpose of experimentation is to determine the relationship between a response variable and the settings of a number of experimental variables (or factors) that are presumed to affect it. Experimental design is the discipline of determining the number and order (spatial or temporal) of experimental runs, and the setting of the experimental variables. 设计的实验用于工业、农业、医学和许多其他活动领域，以检验假设、了解过程并预测未来的反应。实验的主要目的是确定响应变量与假定影响它的许多实验变量（或因素）的设置之间的关系。实验设计是确定实验运行的数量和顺序（空间或时间）以及实验变量设置的学科。 

　　Multivariate Statistics with Advanced Topics 具有高级主题的多元统计 

　　Multivariate data arises whenever several interdependent variables are measured simultaneously. Such high-dimensional data is becoming the rule, rather than the exception in many areas: in medicine, in the social and environmental sciences and in economics. The analysis of such multidimensional data often presents an exciting challenge that requires new statistical techniques which are usually implemented using computer packages. This module aims to give you a good and rigorous understanding of the geometric and algebraic ideas that these techniques are based on, before giving you a chance to try them out on some real data sets. 每当同时测量几个相互依赖的变量时，就会出现多变量数据。这种高维数据正在成为许多领域的规则，而不是例外：医学、社会和环境科学以及经济学。对这种多维数据的分析通常会带来令人兴奋的挑战，需要新的统计技术，而这些技术通常使用计算机软件包来实现。本模块旨在让您对这些技术所基于的几何和代数思想有一个良好而严格的理解，然后让您有机会在一些真实数据集上进行尝试。 

　　Statistical Frontiers 统计前沿 

　　This module is also taken by PhD students in the Warwick Centre for Doctoral Training in Mathematics and Statistics. Each topic will be presented by a different lecturer, who is an expert in the research area. The lectures are intended to introduce a particular research topic, provide a short overview and stimulate your interest in this particular area. Taken as a whole, the module gives a (necessarily partial and incomplete) idea of the breadth of the research interests and expertise within the Department and should thus help you discover the broadness of research areas in statistics and probability that are at the cutting edge of interest. 沃里克数学和统计学博士培训中心的博士生也学习该模块。每个主题将由不同的讲师介绍，他是研究领域的专家。这些讲座旨在介绍一个特定的研究主题，提供一个简短的概述并激发您对该特定领域的兴趣。总的来说，该模块提供了一个（可能是部分和不完整的）该部门研究兴趣和专业知识的广度，从而帮助您发现处于前沿的统计和概率研究领域的广泛性兴趣。 

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