日本語 English
| 開講年度/ Academic YearAcademic Year |
20232023 |
| 科目設置学部/ CollegeCollege |
経営学研究科/Graduate School of BusinessGraduate School of Business |
| 科目コード等/ Course CodeCourse Code |
自動登録/automatic registrationautomatic registration |
| テーマ・サブタイトル等/ Theme・SubtitleTheme・Subtitle |
Survey Methods and Quantitative Analysis |
| 授業形態/ Class FormatClass Format |
対面（一部オンライン）/Face-to-face (partially online)Face-to-face (partially online) |
| 授業形態（補足事項）/ Class Format (Supplementary Items)Class Format (Supplementary Items) |
|
| 授業形式/ Class StyleCampus |
|
| 校地/ CampusCampus |
池袋/IkebukuroIkebukuro |
| 学期/ SemesterSemester |
秋学期他/Fall OthersFall Others |
| 曜日時限・教室/ DayPeriod・RoomDayPeriod・Room |
|
| 単位/ CreditCredit |
22 |
| 科目ナンバリング/ Course NumberCourse Number |
MIB5011 |
| 使用言語/ LanguageLanguage |
英語/EnglishEnglish |
| 履修登録方法/ Class Registration MethodClass Registration Method |
自動登録/Automatic RegistrationAutomatic Registration |
| 配当年次/ Grade (Year) RequiredGrade (Year) Required |
配当年次は開講学部のR Guideに掲載している科目表で確認してください。配当年次は開講学部のR Guideに掲載している科目表で確認してください。 |
| 先修規定/ prerequisite regulationsprerequisite regulations |
|
| 他学部履修可否/ Acceptance of Other CollegesAcceptance of Other Colleges |
|
| 履修中止可否/ course cancellationcourse cancellation |
|
| オンライン授業60単位制限対象科目/ Online Classes Subject to 60-Credit Upper LimitOnline Classes Subject to 60-Credit Upper Limit |
|
| 学位授与方針との関連/ Relationship with Degree PolicyRelationship with Degree Policy |
|
| 備考/ NotesNotes |
|
| テキスト用コード/ Text CodeText Code |
KN004 |
Students will master the fundamentals of survey techniques and statistical analysis in the business context, as well as understand the uses and limitations of survey research.
Lectures will cover important topics on survey techniques and statistical analysis, including matching research design with ontology, designing questions and survey format, sampling and data collection, hypothesis testing, ANOVA, regression analysis, and factor analysis. Challenges such as survey error and nonresponse bias will also be discussed. Students will also have the opportunity to become acquainted with statistical analysis tools by trying them in class under instructor supervision. All students will apply what they have learned by undertaking a survey research project, writing up the results to submit as a final report, and presenting their progress in slide presentations at the midterm (discussing research design) and at the conclusion of the course (discussing the entire project including analysis and results).
※Please refer to Japanese Page for details including evaluations, textbooks and others.
Students will master the fundamentals of survey techniques and statistical analysis in the business context, as well as understand the uses and limitations of survey research.
Lectures will cover important topics on survey techniques and statistical analysis, including matching research design with ontology, designing questions and survey format, sampling and data collection, hypothesis testing, ANOVA, regression analysis, and factor analysis. Challenges such as survey error and nonresponse bias will also be discussed. Students will also have the opportunity to become acquainted with statistical analysis tools by trying them in class under instructor supervision. All students will apply what they have learned by undertaking a survey research project, writing up the results to submit as a final report, and presenting their progress in slide presentations at the midterm (discussing research design) and at the conclusion of the course (discussing the entire project including analysis and results).
| 1 | Overview and Introduction |
| 2 | Ontology, Purposes of Survey Research, Sampling |
| 3 | Sampling Error; Nonresponse Bias |
| 4 | Survey Questions |
| 5 | Validity; Survey Design |
| 6 | Survey Interviewing; Preparing Data for Analysis; Ethical Issues; Reporting Survey Research |
| 7 | Midterm presentations of Research and Survey Design |
| 8 | Midterm presentations of Research and Survey Design (II) |
| 9 | Statistical Analysis |
| 10 | Statistical Analysis (II) |
| 11 | Regression Analysis |
| 12 | Data Analysis Workshop |
| 13 | Final Research Presentations (I) |
| 14 | Final Research Presentations (II) |
板書 /Writing on the Board
スライド（パワーポイント等）の使用 /Slides (PowerPoint, etc.)
上記以外の視聴覚教材の使用 /Audiovisual Materials Other than Those Listed Above
個人発表 /Individual Presentations
グループ発表 /Group Presentations
ディスカッション・ディベート /Discussion/Debate
実技・実習・実験 /Practicum/Experiments/Practical Training
学内の教室外施設の利用 /Use of On-Campus Facilities Outside the Classroom
校外実習・フィールドワーク /Field Work
上記いずれも用いない予定 /None of the above
Students should review material before class, and come prepared to work on computer-based quantitative data analysis.
| 種類 (Kind) | 割合 (%) | 基準 (Criteria) |
|---|---|---|
| 平常点 (In-class Points) | 100 |
最終レポート(Final Report)(40%) Midterm Research Presentation(30%) Final Research Presentation(30%) |
| 備考 (Notes) | ||
| その他 (Others) | |||||
|---|---|---|---|---|---|
| None |