Big Data Analytics
MBA Data Course at Business School of NJU
Big Data Analytics for MBA,
Business School, Nanjing University
Spring,2024
Instructor: Dr. Zhaopeng Qu
Schedual for Lectures
| No | Date | Time | Content | Slides |
|---|---|---|---|---|
| 1 | 3/9/2024 | 9:00am-12:00am | Introduction | Lec0 |
| 2 | 3/9/2024 | 13:30pm-16:30pm | Causal Inference and RCTs | Lec1 |
| 3 | 3/16/2024 | 9:00am-12:00am | OLS Regression and Causality(I) | Lec2 |
| 4 | 3/16/2024 | 13:30pm-16:30pm | OLS Regression and Causality(II) | Lec3 |
| 5 | 3/23/2024 | 9:00am-12:00am | Quasi-Experimental Methods(I) | Lec4 |
| 6 | 3/23/2024 | 13:30pm-14:30pm | Quasi-Experimental Methods(II) | Lec5 |
Schedual for Research Proposal and Final Exam
| Items | Date | Due Time |
|---|---|---|
| 研究项目分组 | 3/9/2024 | 17:00pm之前 |
| 研究题目口头汇报 | 3/16/2024 | 24:00pm之前 |
| 研究计划课堂汇报 | 3/23/2024 | 14:30pm-17:30pm |
Guide to Research Projects(Proposal)（期末研究计划指南）
Course Description
Modern organizations are collecting and scientifically analyzing target customer information to make accurate and profound decisions, thus seizing business opportunities. Whether businesses, governments, hospitals, or schools, relying solely on intuition and experience for decision making is a thing of the past. Nowadays, business managers increasingly depend on data analytics. Numerous companies are extensively utilizing data analytics in marketing, production, and even human resources. This necessitates new-generation decision-makers to adopt a modern data analytics mindset.
This course will use numerous engaging decision cases from various organizations to teach how to handle and analyze large data using scientific and unified thinking. It further introduces the principles of statistical and econometric methods - the most powerful tools for data analysis. Through teacher explanations, machine exercises, and simulated analysis projects, the course aims to transition everyone from concepts and theory to practical data analysis, enhancing their ability to handle and analyze real-world data issues.
The ultimate goal of this course is to broaden students’ perspectives, stimulate innovative thinking, and develop hands-on skills, enabling them to effectively use data analysis thinking in their work, thereby enhancing the creativity and precision of management decisions.
Main Content
Slides(课堂讲义 Spring 2022)
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3/6 Introduction: Lecture 0
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3/6 Causal Inference and RCTs: Lecture 1
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3/13 OLS Regression and Causality: Lecture 2
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3/13 Quasi-Experimental Methods(I): Instrumental Variables and Regression Discontinuity Lecture 3
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3/20 Quasi-Experimental Methods(II): Panel Data, Difference-in-Differences, Synthetic Control Lecture 4
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3/20 Machine Learning and Prediction:Lecture5
Computer Lab Exercise(上机练习）
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Pre Installation:(安装R和RStudio)
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Introduction to R
Online Courses for R(免费的在线R课程）
I am working on an application to free online courses for R and Python for our class. Hopefully, we could get a positive result. Please wait for a while.