《多元统计分析》课程教学资源（阅读材料）A visual tour of interactive graphics with R

《多元统计分析》课程教学资源（阅读材料）A Survey on Multivariate Data Visualization

《多元统计分析》课程教学资源（阅读材料）30 Years of Multidimensional Multivariate Visulization

中国科学技术大学：《多元统计分析》课程教学资源（课件讲义）第二讲 多元数据的可视化技术

中国科学技术大学：《多元统计分析》课程教学资源（课件讲义）第一讲 简介及描述性统计（主讲：张伟平）

《实用统计软件》课程教学资源（阅读材料）Dan Bruns, Chattanooga, TN, An Introduction to the Simplicity and Power of SAS/Graph

1 Introduction 2 SAS Language 2.1 Proc Step and Data Step 2.2 SAS Logical Library 2.2.1 Access SAS file 2.2.2 View SAS library and file 3 SAS Programming 3.1 Reading data by DATA STEP 3.2 Output format 3.3 Manipulate datasets 3.3.1 SET statement 3.3.2 SORT proc 3.4 Logical statements 3.4.1 IF-THEN statement 3.4.2 SELECT-WHEN statement 3.4.3 DO-ENDS statement 3.4.4 DO-WHILE DO-UNTIL statement 3.5 OPERATIONS 4 Basic statistical analysis 4.1 Descriptive Statistics Proc 4.1.1 MEANS proc 4.1.2 SUMMARY proc 4.1.3 UNIVARIATE proc 4.1.4 TABULATE PROC 4.1.5 GCHART proc 4.1.6 GPLOT proc 4.2 INFERENTIAL Statistics 4.2.1 T-TEST 4.2.2 Chi-square tests 4.2.3 Correlation 4.2.4 Regression

1 Programming 1.1 M file 1.1.1 Program Control Statements 1.1.2 M-File Functions 1.2 anonymous functions 2 Computational statistics with Matlab 2.1 Functions on Probability and Statistics 2.1.1 Probability distribution 2.1.2 Descriptive statistics 2.1.3 Statistical plotting 2.1.4 Linear model 2.1.5 Multivariate Statistics 2.2 Monte Carlo with Matlab 2.2.1 Monte Carlo Assessment of Hypothesis Testing 2.2.2 MCMC with matlab 3 Symbolic computation with matlab 3.1 Creating Symbolic Variables and Expressions 3.2 Calculus 4 Optimization 4.1 Unconstrained Minimization Example 4.2 Nonlinear Inequality Constrained Example

1 Introduction 1.1 GUI and Basic functions 1.1.1 Command Window 1.1.2 Command History 1.1.3 MatLab Help 2 Data in MatLab 2.1 Manipulating data 2.1.1 Creating Objects 2.1.2 Operators 3 Graphics 3.1 Use plotting tools 3.2 Use the command interface 3.2.1 Basic plots 3.2.2 Adding Plots to an Existing Graph 3.2.3 Multiple Plots in One Figure 3.2.4 Controlling the Axes 3.2.5 Axis Labels and Titles 3.3 Mesh and Surface Plots 3.4 Creating Specialized Plots 3.5 Advanced plotting

1 Numerical optimization methods in R 1.1 Root-finding in one dimension 1.1.1 Bisection method 1.1.2 Brent’s method 1.1.3 Newton’s method 1.1.4 Fisher scoring 1.2 multivariate optimization 1.2.1 Newton’s method and Fisher scoring 1.3 Numerical Integration 1.4 Maximum Likelihood Problems 1.5 Optimization Problems 1.5.1 One-dimension Optimization 1.5.2 multi-dimensional Optimization 1.6 Linear Programming