加入收藏  || English Version 
 
研究生课程《数据分析与统计计算》教学大纲

  发布日期:2016-12-20  浏览量:332


研究生课程教学大纲

课程编号:Math2103

课程名称:数据分析与统计计算

英文名称:Data Analysis and Computational Statistics Methods

 

 

开课单位:安大澳门赌搏网站大全

开课学期:秋

课内学时:36

教学方式:英文讲授

适用专业及层次:统计学专业与计算数学专业硕士生

考核方式:考试

预修课程:概率论与数理统计、线性代数

 

一、教学目标与要求

This course aims to prepare students to input, verify, organise, modify, combine, analyse and present data using a range of computing and statistical methods implemented in thegeneral purpose statistical packages. Topics include generation of random numbers,Monte Carlo methods, optimization methods, numerical integration, resampling methods such as the Bootstrap and the Jackknife, and advanced Bayesian computational tools such as the Gibbs sampler, Metropolis Hastings, the method of auxiliary variables, marginal and conditional data augmentation, slice sampling, exact sampling, and reversible jump MCMC. Computer programming exercises apply the methods discussed in class

 

二、课程内容与学时分配

  • Chapter 1 Preface
  • Chapter2 Turning Data Into Information4 课时)
  • Raw Data
  • Types of Data
  • Summarizing One or Two Categorical variables
  • Finding Information in Quantitative Data
  • Pictures for Quantitative Data
  • Numerical Summaries of Quantitative Variables
  • Bell-Shaped Distributions of Number

 

  • Chapter 3 Gathering Useful Data4 课时)
  • Description or Decision? using Data Wisely
  • Speaking the Language of Research Studies
  • Designing a Good Experiment
  • Designing a Good Observation
  • Difficulties and Disasters in Experiments and Observational Studies
  •  
  • Chapter 4 sampling 4 课时)
  • The beauty of Sampling
  • Simple Random Sampling and Randomization
  • Other Sampling Methods
  • Difficulties and Disasters in Sampling
  • How to Ask Survey Questions
  • 􀂃
  •  Chapter 5 Relationships Between Quantitative Variables4 课时)
  •  Looking for Patterns with Scatterplots
  • Describing Linear Patterns with a Regression Line
  •  Measuring Strength and Direction with Correlation
  • Why the Answers May Not Make Sense
  • Correlation Does Not Prove Causation
  •  
  •  Chapter 6 Relationships Between Categorical Variables4 课时)
  • Displaying relationships between Categorical Variables
  • Risk, Relative Risk, Odds Ratio, and Increased Risk
  • Misleading Statistics About Risk
  • The Effect of a Third Variable and Simpson’s Paradox
  • Assessing the Statistical Significance of a 2*2 Table
  •  
  • Chapter 7 Computational Statistics Experiments designing
  • Topic 1: Generation of random numbers, 2 课时)
  • Topic 2: Monte Carlo methods, optimization methods, 2 课时)
  • Topic 3: Numerical integration, resampling methods such as the Bootstrap and
  • the Jackknife, 2 课时)
  • Topic 4: Advanced Bayesian computational tools such as the Gibbs sampler2
  • 课时), Metropolis Hastings2 课时), the method of auxiliary variables2
  • 时), marginal and conditional data augmentation, slice sampling2 课时), exact
  • sampling, and reversible jump MCMC2 课时)

 

四、教材

Springer Handbook of Computational Statistics Concepts and Methods

Editors: Gentle, James E., Härdle, Wolfgang Karl, Mori, Yuichi (Eds.)

主要参考书

1J. A. Rice, Mathematical Statistics and Data Analysis, 2nd edition, Duxbury Press,

1994, ISBN 0-534-20934-3.

2. G. W. Snedecor, W. G. Cochran, Statistical Methods, Iowa State University Press,

8th Edition, 1989, ISBN 0-813-81561-4.

 

大纲撰写负责人:毛军军

授课教师:毛军军,王学军,杨联强,杨文志,汪世界,沈燕,吴涛

 

打印此页】【顶部】【关闭
   
版权所有 2019 澳门赌搏网站大全 All rights reserved 皖ICP备05018241号
地址:安徽省合肥市九龙路111号澳门新莆京娱乐网站磬苑校区理工楼H楼 邮编:230601 E-mail:math@ahu.edu.cn
访问统计:自2013年9月1日以来总访问:1000  后台管理


XML 地图 | Sitemap 地图