GMBA 7098: Statistics and Data Analysis, Fall 2014

Instructor: Ling-Chieh Kung
Department of Information Management
National Taiwan University

Statistics and data analysis are probably playing the most important roles in business analytics nowadays. With the ability to conduct scientific statistical studies and systematically analyze data, managers will be able to understand more about their customers, suppliers, competitors, and the business environment. The insights may then facilitate better decision making and help a company to attain competitive advantages. In this fundamental course in the Global MBA (GMBA) program, we will focus on the techniques for conducting basic statistical studies and data analysis. The hope is that students will be capable of doing scientific data analyses in their future GMBA courses and after graduations. Time will be spent on tools, applications, as well as theories. R, one of the most popular programming languages for data analysis, will be taught and used throughout this course. Students will learn how to write R programs to play with data. For at least part of this course, we will adopt the "flipped classroom" principle, which may be new to some students. Please pay attention to the syllabus to get an idea about the design of this course.

This is a required course offered in the GMBA program in National Taiwan University. The GMBA office does not allow non-GMBA students to take or audit this course.

Basic information

Instructor
  • Ling-Chieh Kung (¤Õ¥O³Ç).
  • E-mail: lckung(AT)ntu.edu.tw.
  • Office: Room 413, Management Building II.
  • Tel: 02-3366-1176.
  • Office hour: 9:00-10:30am, Thursday.
Teaching assistants
  • Ian Zhong (Áé«a¦t). E-mail: r03725040(AT)ntu.edu.tw.
  • Ho Ho (¦ó¥Ý). E-mail: r03725041(AT)ntu.edu.tw.
Lectures
  • 2:20pm-5:20pm, Monday.
  • The case study classroom, Management Building I.
On-line resources
  • To check grades: CEIBA.
  • To download or link to materials: This website.
  • To discuss: the bulletin board "NTUIM-lckung" on PTT.

Syllabus

For a detailed description about this course, including course policies, grading rules, references, etc., please see the syllabus. Whenever there is an update, a new version will be posted with a short note describing the update.

Posted on Syllabus Notes
2014/8/21 Link The basic planning of this course

Course outline

There are four modules in this course: foundations, inferential statistics, advanced techniques, and applications. We will spend five, four, and five lectures in the first three modules to introduce basic theories and methods. Each module is then concluded with a case study. The last module includes a guest speaker's talk about applying statistics and data analysis. Students' presentations for their final projects then conclude this course.

Schedule

Week Lecture Date Materials Videos Handouts Topics
1 2014/9/15 Slides N/A N/A Introduction
2 2014/9/22 Slides Playlist Files Descriptive statistics (1)
3 2014/9/29 N/A Playlist N/A Descriptive statistics (2)
-- -- Slides N/A N/A A story of data analysis
4 2014/10/6 Slides Playlist N/A Introduction to Probability (1)
5 2014/10/13 N/A N/A N/A Case 1 presentations
6 2014/10/20 Slides Playlist Codes Introduction to Probability (2)
7 2014/10/27 Slides Playlist N/A Sampling and sampling distribution
8 2014/11/3 Slides Playlist N/A Estimations
9 2014/11/10 N/A N/A N/A Midterm exam
10 2014/11/17 Slides N/A N/A Hypothesis testing (1)
11 2014/11/24 Slides N/A Data Hypothesis testing (2)
12 2014/12/1 Slides Playlist Data Regression analysis (1)
13 2014/12/8 N/A N/A Data Regression analysis (2)
14 2014/12/15 N/A N/A N/A Case 3 presentations
15 2014/12/22 Slides N/A N/A Feedback for Case 3
16 2014/12/29 Slides N/A N/A Review
17 2015/1/5 N/A N/A Project presentations (1)
18 2015/1/12 N/A N/A N/A Project presentations (2)

Exams

The midterm exam problems are here. The suggested solution is here.

Project

The description of the final project is here.

Case studies

Please see CEIBA.

Homework

Homework Topic Release date Solution Script
Homework 1 Descriptive statistics 2014/9/29 Solution 1 Script 1
Homework 2 Probability (1) 2014/10/6 Solution 2 N/A
Homework 3 Probability (2) 2014/10/20 Solution 3 N/A
Homework 4 Sampling distribution and estimations 2014/11/5 Solution 4 N/A
Homework 5 Hypothesis testing 2014/12/3 Solution 5 Script 5
Homework 6 Regression (1) 2014/12/4 Solution 6 Script 6
Homework 7 Regression (2) 2014/12/12 Solution 7 Script 7

Note. No homework requires a submission. These problems are simply for you to practice on. Solutions will be provided shortly after the problems are posted.

Data sets

Data Description
Link Wholesale data in Portugal

Note. If clicking on the link does not download the data set as a plain text (TXT) file, you may right click the link and then save it. Alternatively, you may copy everything that appear on your browser and then paste them into an empty plain text (TXT) file. Then saving the file with an appropriate file name completes the task.

Documentations

Document Description
Link R installation and setup for Windows
Link R installation and setup for Mac
Link Common mathematical notations and operations
Link Data Analysis in MS Excel
Link Introduction to Logistic Regression