シラバス参照

開講年度(Academic Year) 2021 
科目コード/科目名
(Course Code / Course Title)
その他/2年次演習1
(Seminar1(2nd year)) 
テーマ/サブタイトル等
(Theme / Subtitle)
Data Analysis for Finance and Marketing 
担当者 (Instructor) 竹澤 伸哉(TAKEZAWA NOBUYA) 
時間割 (Class Schedule) 春学期 (Spring Semester) 木曜日(Thu) 3時限(Period 3) 5206(Room)
単位 (Credit) 2単位(2 Credits) 
科目ナンバリング
(Course Number)
GBU2011 
使用言語
(Language)
英語
(English) 
備考 (Notes) コンセントレーション:マーケティング領域, アカウンティング&ファイナンス領域 
テキスト用コード (Text Code) BT319 



授業の
目標
Course
Objectives
After completing the seminar, students should have the skills to undertake and critically assess introductory level data analysis in financial economics and marketing. This is the first in a series of seminars designed to provide students with a working knowledge in quantitative methods (and tools) for business. 
 
授業の
内容
Course
Contents
Each session will involve a student presentation on an assigned topic and a follow-up discussion by the instructor or a short in-class exercise using EXCEL. In this new era of "Big Data," the ability to summarize data into useful information for decision making is crucial for success in business. The course provides an introduction to summarizing the data in the form of key indicators (descriptive statistics). Students also learn methods for analyzing the data: regressions and conjoint analysis. 
 
授業計画
Course
Schedule
1. Overview 
2. Turning Data into Information: Descriptive Statistics-variables 
3. Turning Data into Information: Descriptive Statistics-graphs 
4. Turning Data into Information: Descriptive Statistics-mode, median, mean 
5. Turning Data into Information: Descriptive Statistics-standard deviation, variance 
6. Turning Data into Information: Descriptive Statistics-correlation 
7. Relationships Between Quantitative Variables: The Regression Model 
8. Relationships Between Quantitative Variables: The Regression Model 
9. Dummy Variables and Regressions 
10. Understanding Conjoint Analysis: An Introduction 
11. Understanding Conjoint Analysis: An Introduction 
12. Case: Conjoint Analysis 
13. Catch-up 
14. Wrap-up 
授業時間外
(予習・復習
等)の学習
Study
Required
Outside
of Class
Read assigned chapter carefully before coming to class. 
成績評価
方法・基準
Evaluation
種類(Kind) 割合(%) 基準(Criteria)
平常点(In-class Points) 100  %
Presentations & Participation(40%) 、Assignments(40%) 、Case Analysis(20%)
テキスト
Textbooks
No 著者名
(Author/Editor)
書籍名
(Title)
出版社
(Publisher)
出版年
(Date)
ISBN/ISSN
1. J. Utts and R. Heckard  Mind on Statistics 5th ed.   Brooks  2015  978-1305649811 
2. Anderson・Sweeney・Williams  Essentials of Modern Business Statistics   Engage Learning  2015   
3. G. Privitera  Essential Statistics for the Behavioral Sciences   Sage  2019  9781544328010 
その他(Others)
参考文献
Readings
No 著者名
(Author/Editor)
書籍名
(Title)
出版社
(Publisher)
出版年
(Date)
ISBN/ISSN
1. 内田 学、 兼子 良久  『文系でもわかる ビジネス統計入門』   東洋経済新報社  2010   
その他(Others)
TBA
その他
(HP等)
Others
(e.g. HP)
This seminar is conducted in English. Detailed course outline distributed second week of class. 
注意事項
Notice
 


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