Market and Economic Research and Analysis
Market and Economic Research and Analysis
Fall 2019
Tuesday 6pm to 8:45pm
Location: SCI 117
Cheonghum Park
Department of Economics
270 Bay State Road, Room 514
Email: chpark@bu.edu
Fall 2019
Tuesday 6pm to 8:45pm
Location: SCI 117
Cheonghum Park
Department of Economics
270 Bay State Road, Room 514
Email: chpark@bu.edu
This course is an introduction to the world of market research with a focus on extracting meaningful data from text and the Internet. Students should leave the class with a broad understanding of the structure of various market research objectives and methodologies and with the confidence in using modern web scraping and text analysis tools that are becoming widely popular in real-world business as well as in the academia. In-class hands-on experiences, forum discussions, quizzes, and group-based presentations throughout the course will reinforce students' learning of how to use data analysis in the context of market and economic research. Topics include market research theory, primary data collecting through web scraping and text analysis, data wrangling, basic statistics, and data visualization. Python will be extensively used throughout the course but no prior experience to the language is required.
The classroom sessions are a combination of lectures and experiential learning. To ensure effective utilization of lecture time, you are required to read the materials before they are covered in class and bring your computer with the required software installed and the required data sets downloaded.
This course has been fully updated by Cheonghum Park in Summer 2019.
1) Required text: Stromp, S. (2019), Market Research Essentials, Stukent
2) Course website: Blackboard Learn - To access your course website, go to http://learn.bu.edu and select AD856 (2019 Fall)
3) Lecture notes: Lecture notes will be uploaded to the course website after each class.
4) Computer: You are required to bring a laptop to every class
5) Required software: Python 3.7 & Jupyter Notebook - I strongly recommend installing Python via Anaconda Distribution(https://www.anaconda.com/distribution), which includes both Python and Jupyter Notebook as well as other required modules in class. If you have already installed Python through some other channel, pip-install Jupyter Notebook separately using the following code:
python3 -m pip install --upgrade pip
python3 -m pip install jupyter
If you are not familiar with pip, I recommend removing Python from your computer and re-installing via Anaconda Distribution.
Class participation (10%)
Open book quiz (20%)
Online discussion forum (20%)
Team final project (50%)
Students are required to form a group of two to three to work on the final research project. The project should focus on constructing a dataset to solve a clearly-stated research question, applying either web scraping or text analysis or both as a research methodology. You could partially or entirely use any data covered in class over the course of constructing the final data set while including primary or secondary data from other sources is also allowed. The outcome will be graded based on clarity and relevance of the research question, completeness of the final data set, and the effectiveness of the usage of web scraping and/or text analysis tools but not on the selection of the data source. This exercise consists of three different milestones:
1) Three ideas (10 points)
Come up with at least three research questions and concisely describe them on about one page each. You should address the relevance of each research question and list every potential data required in the analysis and where/how to obtain those. We will then discuss the suitability of each idea via email and choose one.
2) Interim presentation (15 points)
Describe the current state of the project in less than 10 minutes. The presentation should briefly describe the elements of the initial proposal of the idea and discuss some of the challenges that you have been facing. You may discuss any change in the topic or direction of the project with me before the submission of the interim presentation slides but not afterward.
3) Final presentation (25 points)
You should present the outcome of the project in class in 20 to 30 minutes using powerpoint slides and submit the slides with a brief evaluation of each of your teammates’ contribution. The final project will be evaluated based on the in-class presentation but not on the submitted slides. Focus on delivering every element of the grading criteria above during the presentation.
You are expected to abide by the Boston University academic conduct code. Any work you submit has to be your own or your fair share of a group project. It is your responsibility, as a student, to be aware of the code’s contents. For the full text of the academic conduct code, please go to http://www.bu.edu/met/for- students/met-policies-procedures-resources/academic-conduct-code/