7.1 Learn what Big Data is and how it is changing the world of analytics 7.2 Understand the motivation for and business drivers of Big Data analytics 7.3 Become familiar with the wide range of enabling technologies for Big Data analytics 7.4 Learn about Hadoop, MapReduce, and NoSQL as they relate to Big Data analytics 7.5 Compare and contrast the complementary uses of data warehousing and Big Data technologies 7.6 Become familiar with select Big Data platforms and services 7.7 Understand the need for and appreciate the capabilities of stream analytics 7.8 Learn about the applications of stream analytics

8.1 Explore some of the emerging technologies that may impact analytics, business intelligence (BI), and decision support 8.2 Describe the emerging Internet of Things (IoT) phenomenon, potential applications, and the IoT ecosystem 8.3 Describe the current and future use of cloud computing in business analytics 8.4 Describe how geospatial and location-based analytics are assisting organizations 8.5 Describe the organizational impacts of analytics applications 8.6 List and describe the major ethical and legal issues of analytics implementation 8.7 Identify key characteristics of a successful data science professional

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

一、高级统计学研究的对象 多指标或多变量数据 企业管理:产值、单位成本、原 材料消耗、工资、劳动生产率、 销售收入、利润、全要素生产率 居民家庭消费:家庭收入、家庭 人口、阶层、中高档消费品支出 等等

➢学习内存管理模型与其数据结构 ➢使用显示空闲链表实现一个32位系统堆内存分配器 ➢了解基础的内存管理算法 ➢尝试更高级的内存分配算法

上述双方协商同意，特签订本协议书，以此为证。 鉴于许可方开发并拥有一个取名为“ ”的计算机系统，一个集成数据 库办公室管理和财务控制系统的所有权，并且鉴于被许可方希望获得上述系统并在 其总部加以使用，许可方愿意向被许可方提供上述系统并发给使用许可证

6.1概 例: 飞机的最大速度有设计标准450m/s 检验进口钢板平均厚度定为5mm 我国出口一批罐头,标称重量500g,据以往经验, 标准公差为20g;现抽100罐,x=505g,问是否可 以认为合乎标准?

一 、SA系统简介 SA是Statistical Analysis System”的缩写,是一个用来管理分析数据和编写报告 的组合软件系统。其基本部分是SAS/BASE软件。1966年,美国 North Carolina州立大学 开始开发SAS统计软件包,1976年该系统完成同时成立SAS研究所

5.1点估计 5.2区间估计概述 5.3区间估计的例子 5.4小样本与T分布 5.5总体比率的估计 5.6样本容量的问题 5.7两正态总体问题 5.8抽样的方法

第一章 Delphi77.0集成开发环境 第二章面向对象基础知识和 Windows程序开发初步 第三章 Object Pascal语言基础 第四章常用控件的使用 第五章程序的调试和异常处理 第六章数据库程序开发 第七章项目实例1系部图书管理系统 第八章项目实例2一小区物业管理系统 第九章项目实例3- DelphiExcel控制 第十章项目实例4-DVD租赁管理系统