统计学

本课程将教你各种统计技术背后的理论,以及如何在专业统计人员每天面对的场景中应用它们。你将发展重要的统计技术和概念的详细工作知识,包括线性和广义线性建模、贝叶斯统计、时间序列和机器学习。你将学习如何从数据中分析和得出有意义的结论,并使用统计计算软件R发展你的编程技能。

Statistics

专业介绍

本课程将教你各种统计技术背后的理论,以及如何在专业统计人员每天面对的场景中应用它们。你将发展重要的统计技术和概念的详细工作知识,包括线性和广义线性建模、贝叶斯统计、时间序列和机器学习。你将学习如何从数据中分析和得出有意义的结论,并使用统计计算软件R发展你的编程技能。

Program Introduction

This course will teach you the theories behind a variety of statistical techniques, and how to apply them in scenarios that professional statisticians face every day.

You’ll develop a detailed working knowledge of important statistical techniques and concepts, including linear and generalised linear modelling, Bayesian statistics, time series and machine learning. You’ll learn how to analyse and draw meaningful conclusions from data, and develop your programming skills using the statistical computing software R.

This course also includes modules on how to collect data and design experiments, and the role of statistics in clinical trials.

Around one-third of the course is devoted to your dissertation. This may focus on investigating a data set, or a more theoretical or methodological topic. The aim is to give you skills to include on your CV, such as planning and researching a project, data acquisition, problem specification, analysis and reporting your findings.

Dissertation topics are often provided by external clients – for example, pharmaceutical companies or sports modelling organisations. Distance learning students often come with projects designed by their employer.

所属大学 谢菲尔德大学
关联学科 数学
开学时间 9月
学制 1 年
学费 27,670 GBP
项目网址 https://www.sheffield.ac.uk/postgraduate/taught/courses/2022/statistics-msc

申请要求

专业领域:相关专业如数据科学,数学,统计学。先修科目:1 数学类科目如代数/线性代数,微积分,数学方法。2 概率类科目如Markov chains/processes,概率理论/模型,Stochastic processes/models/modelling。3 统计类科目如应用统计,贝叶斯统计,计算统计,数据挖掘/分析,计量经济,医学统计,多变量统计,编程语言(R,Python),样本与调查设计,统计分析,时序。

语言要求

IELTS

总分要求: 6.5
分项要求: 听力: 6 | 阅读: 6 | 写作: 6 | 口语: 6

TOEFL

总分要求: 88
分项要求: 听力: 19 | 阅读: 20 | 写作: 19 | 口语: 22

课程设置

中文课程名 英文课程名
核心模块 Core modules
统计学家的工具包 The Statistician's Toolkit
贝叶斯统计和计算方法 Bayesian Statistics and Computational Methods
机器学习 Machine Learning
抽样理论与实验设计 Sampling Theory and Design of Experiments
时间序列 Time Series
医学统计 Medical Statistics
论文 Dissertation
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