海南大学：《离散数学》课程教学大纲 Discrete Mathematic

1 What Is Statistics? 1 2 Probability 20 3 Discrete Random Variables and Their Probability Distributions 86 4 Continuous Variables and Their Probability Distributions 157 5 Multivariate Probability Distributions 223 6 Functions of Random Variables 296 7 Sampling Distributions and the Central Limit Theorem 346 8 Estimation 390 9 Properties of Point Estimators and Methods of Estimation 444 10 Hypothesis Testing 488 11 Linear Models and Estimation by Least Squares 563 12 Considerations in Designing Experiments 640 13 The Analysis of Variance 661 14 Analysis of Categorical Data 713 15 Nonparametric Statistics 741 16 Introduction to Bayesian Methods for Inference 796

西点军校：《数学建模》课程教学课件（教材讲义）ma103model Modeling in Discrete Dynamical Systems

7.1 Consistence, Convergence and Stability of Discretized Equations 7.1.1 Truncation error and consistence(相容性） 7.1.3 Round off error （舍入误差）and stability （稳定性） of initial problems（初值问题） 7.1.4 Examples 7.1.2 Discretization error（离散误差） and convergence(收敛性） 7.2 von Neumann Method for Analyzing Stability of Initial Problems 7.2.1 Propagation of error vector with time 7.2.2 Discrete Fourier expansion 7.2.3 Basic idea of von Neumann analysis 7.2.4 Examples of von Neumann analysis 7.2.5 Discussion on von Neumann analysis

《离散数学》课程教学大纲 Discrete mathematics

福州大学：《离散数学》课程教学大纲 Discrete Mathematics

一、二元离散选择模型的经济背景 二、二元离散选择模型 三、二元Probit离散选择模型及其参数估计 四、二元Logit离散选择模型及其参数估计

Chapter 1 Introduction Chapter 2 Entropy & Mutual Information (Shannon’s measure of information) Chapter 3 The Asymptotic Equipartition Property (渐进等同分割性) Chapter 4 Entropy Rates of a Stochastic Process Chapter 5 Coding for Discrete Sources Chapter 6 Channel Capacity Chapter 7 The Gaussian Channel Chapter 8 Rate Distortion Theory Chapter 9 复习

▪ Interpret the mean and standard deviation for a discrete probability distribution ▪ Explain covariance and its application in finance ▪ Use the binomial probability distribution to find probabilities ▪ Describe when to apply the binomial distribution ▪ Discuss the Hypergeometric distribution ▪ Review the Poisson distribution

 生成树  深度优先搜索  广度优先搜索  有向图的深度优先搜索  回溯  最小生成树算法