商业分析课题：大数据统计与建模
在流程优化及战略评估中的应用研究
开始日期：2023-11-04
课时安排：7周在线小组科研学习+5周不限时论文指导学习
Prerequisites
适合人群
适合年级(Grade)：高中生/大学生
适合专业(Major)：
商业分析、数据科学、风险管理、统计学，应用数学等专业或者希望修读相关专业的学生;具有代数及微积分基础的学生优先
Instructor Introduction
导师介绍
Program Background
项目背景
数据具有固有的不确定性，例如：人的感情;天气形势;可再生资源;以及未来预测。尽管存在不确定性，数据仍然包含宝贵的信息。从本质来讲，人类不喜欢不确定性，但简单地忽略这一点可能产生比不确定性本身更多的问题。在大数据时代，高管需要以不同的方式处理不确定性的各个维度。他们需要承认、接受这一点，并确定如何充分利用不确定的数据。大数据的重要作用之一便是可以作为客户和企业之间的双向通道。例如，特斯拉电动车在驾驶和停车时产生大量数据。在行驶中，司机持续地更新车辆的加速度、刹车、电池充电和位置信息。数据也传回工程师以了解客户的驾驶习惯，用于优化汽车性能。本项目旨在探索如果获取更多的不同种类的数据，以及培养数据分析能力，包括软件工具和使用这些数据分析工具的必备技能。
Managers encounter data daily and regularly base their decisions on it. In the published book, “Competing on Analytics: The New Science of Winning”by Harvard Business School Press, Thomas H. Davenport and Jeanne G. Harris reveal how organizations such as Amazon.com, Wal-Mart, Netflix, Capital One, and others use analytics as a tool for competitive differentiation and advantage. Business analytics is the sensible use of data and quantitative models for informing decisions and actions. Business Analytic can help companies make better decisions by showing present and historical data within their business context. Analysts can leverage business analytic to provide performance and competitor benchmarks to make the organization run smoother and more efficiently. Analysts can also more easily spot market trends to increase sales or revenue. Used effectively, the right data can help with anything from compliance to hiring efforts.
Program Description
项目介绍
商业分析和数据建模是商业和工业中有效的管理决策的重要技能。通过对企业的销售、利润和其他关键指标的趋势建模，可以对这些指标的未来进行有效的科学预测。通过数据分析和建模了解可能发生的季节性、年度或任何规模的变化，可以让企业经营有备无患。该项目内容为商业分析核心知识与技能，包括统计分析、概率分布、决策分析、抽样分布、置信区间、假设检验、回归模型等。其中，概率模型侧重不确定性和风险处理;统计分析侧重数据呈现以及如何通过数据获取有用信息和有效推论;优化模型和决策分析侧重运用数据进行决策。学生将在项目中运用Excel或Mintab进行商业数据分析，在项目结束时提交报告，进行成果展示。
Business Analytics and modeling are important skills for effective managerial decision-making in business and industry. Advances in technology (computers, scanners, cell phones) have made a significant amount of data available to managers. Furthermore, business analytics provides a way for businesses to plan for the future. By modeling the trends in a businesses' sales, profits, and other key metrics, these indicators can be projected into the future. Understanding the changes that are likely to occur seasonally, annually, or on any scale allows businesses to better prepare. The techniques learned in this program will help students infer data and as such make better-informed decisions. The program covers statistical analysis, probability distributions, sampling distributions, confidence intervals, hypothesis testing, and regression models. Probability models provide tools to handle uncertainty and risk. The statistical analysis focuses on the presentation of data and techniques to draw useful and valid inferences from data.
Syllabus
项目大纲
描述性统计与离散概率分布 Descriptive statistics; discrete probability distributions
离散与连续概率分布;回报/风险分析 Discrete and continuous probability distributions; return/risk analysis
抽样分布与置信区间估计 Sampling distributions; confidence interval estimation
假设检验 Hypothesis testing about population mean and proportion
简单回归模型与多元回归模型 Simple regression models; multiple regression models
案例分析：供应链优化及战略制定 Case Study
项目回顾与成果展示 Program Review and Presentation
论文辅导 Project Deliverables Tutoring
Program Outcome
项目收获
4周在线小组科研学习+2周不限时论文指导学习 共125课时
项目报告
优秀学员获主导师Reference Letter
EI/CPCI/Scopus/ProQuest/Crossref/EBSCO或同等级别索引国际会议全文投递与发表指导(可用于申请)
结业证书
成绩单
