Faculty of Business Administration

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MAN200FA（経営学 / Management 200）
Seminar 1

Ryosuke IGARI

Class code etc
Faculty/Graduate school Faculty of Business Administration
Attached documents
Year 2022
Class code A4657
Previous Class code
Previous Class title
Term 春学期授業/Spring
Day/Period 木4/Thu.4,木5/Thu.5
Class Type
Campus 市ヶ谷
Classroom name 各学部・研究科等の時間割等で確認
Grade 2
Credit(s) 3
Notes ※　原則春学期、秋学期連続で受講してください。
Open Program
Open Program (Notes)
Global Open Program
Interdepartmental class taking system for Academic Achievers
Interdepartmental class taking system for Academic Achievers (Notes)
Class taught by instructors with practical experience
SDGs CP
Urban Design CP
Diversity CP
Learning for the Future CP
Carbon Neutral CP
Chiyoda Campus Consortium
Admission year
Category (2019～) 演習
Category (～2018) 選択
演習

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Outline (in English)

[Course outline]
In recent years, the marketing / business data environment called "big data" has been improved, the word "data scientist" is born, and marketing　data analysis are required even at the business. The purchase history at the stores of the consumer is accumulated as POS or ID-POS data, and the internet browsing history etc. by the PC, the smartphone, etc. are also recorded as the access log data. Then, each company uses such data to make marketing decisions such as deciding price, advertisement input amount, sales promotion at shop front, etc.
In this course, we will learn skills of marketing theory and data analysis, analyze actual marketing data, and acquire practical skills. It also aims to acquire the ability to set themselves and deal with themes through marketing and data analysis, and to develop presentation skills to present and share results.


[Learning Objectives]
Students will acquire basic knowledge of marketing science and skills of marketing data analysis using statistical software.
Students can make a presentation using the results of analysis.


[Learning activities outside of classroom]
Students will be assigned to a chapter of a textbook and will give a presentation.
In the exercise, students will actually perform analysis on their own PCs using the statistical software R. (Preparation of materials is required.)
Students will work on themes and write a paper.
The standard preparation and review time for this class is 2 hours each.


[Grading Criteria/Policy]
Attendance and participation in class discussions:30%.
Group work and individual reports and final reports:40%.
Senior Thesis or Graduation Thesis: 30%.

Default language used in class

日本語 / Japanese