矩的几种定义 简单的矩方法 一般的矩方法 矩方法与最大似然法和最小二乘法的比较

4.1 Kruskal-Wallis 秩和检验 4.2 正态记分检验* 4.3 Jonckheere-Terpstra检验样本不独立 4.4 区组设计数据分析回顾 4.5 完全区组设计：Friedman秩和检验 4.6 Kendall协同系数检验 4.7 完全区组设计：Cochran检验 4.8 完全区组设计：Page检验 4.9 不完全区组设计：Durbin检验

6.1 Understand the applications of prescriptive analytics techniques in combination with reporting and predictive analytics 6.2 Understand the basic concepts of analytical decision modeling 6.3 Understand the concepts of analytical models for selected decision problems, including linear programming and simulation models for decision support 6.4 Describe how spreadsheets can be used for analytical modeling and solutions 6.5 Explain the basic concepts of optimization and when to use them 6.6 Describe how to structure a linear programming model 6.7 Explain what is meant by sensitivity analysis, what-if analysis, and goal seeking 6.8 Understand the concepts and applications of different types of simulation 6.9 Understand potential applications of discrete event simulation

方案拟定 测点布置及仪器设备选用 加载等级控制及过程安全控制 数据分析与结构性能评定

5.1 Describe text mining and understand the need for text mining 5.2 Differentiate among text analytics, text mining, and data mining 5.3 Understand the different application areas for text mining 5.4 Know the process of carrying out a text mining project 5.5 Appreciate the different methods to introduce structure to text-based data 5.6 Describe sentiment analysis 5.7 Develop familiarity with popular applications of sentiment analysis 5.8 Learn the common methods for sentiment analysis 5.9 Become familiar with speech analytics as it relates to sentiment analysis

似然函数，最大似然估计量 指数与高斯概率密度函数的参数确定举 最大似然估计量的方差 不等精度观测结果的并合 解析法 蒙特卡罗法 RCF边界法 图解法

4.1 Define data mining as an enabling technology for business analytics 4.2 Understand the objectives and benefits of data mining 4.3 Become familiar with the wide range of applications of data mining 4.4 Learn the standardized data mining processes 4.5 Learn different methods and algorithms of data mining 4.6 Build awareness of the existing data mining software tools 4.7 Understand the privacy issues, pitfalls, and myths of data mining

检验拟合优度，P-值定义与应用 信号观测的显著程度 皮尔逊的χ2检验 样本、估计量与偏置 估计量的平均值、方差与协方差

本章主要内容： · 综合评分法、综合平衡法、排队打分法； · 水平数不同的正交表的使用，包括直接套用混合正交表、并列法、拟水平法、混合水平有交互作用的正交设计； · 活动水平法、组合因素法；分割试验法；部分追加法

假设，检验统计量，显著水平，功效 两种假设下的统计检验 纽曼-皮尔森引理 如何构造一个检验统计量 Fisher甄别函数与神经网络