Syllabus: 미디어 조사방법론 대학원

기본정보

• 월요일 6:00-8:45
• 교실: 산학원 422-1
• 강의: 김효동 (hkimscil at ajou dot ac dot kr)
• 상담시간: 월/수 4:30-6:00 or by appointment

교과목개요

Basic Statistics와 Multivariate Statistics 분석방법을 이용하는 연구문제를 설계하고 논문을 완성합니다.

교육목표

통계기법을 이용하여 학생들은 아래의 항목에 대해 익히고 이를 연구계획 및 연구에 접목할 수 있어야 합니다.

1. investigating and summarizing previous studies;
2. identifying and re-defining student's research interests;
3. designing a proper research methods;
4. obtaining proper data;
5. analyzing the data with proper methods;
6. developing and articulating the results and findings based on logic and reasons.

수업형식 및 진행

Discussions of readings and assignment
Discussions of students' own research works, which may include

1. investigating previous works based on student's own interests
2. articulating student's research interests and research questions
3. reviewing and identifying research design
4. gathering data
5. analyzing data
6. summing up student's findings

수업운영

• 강의
• 토론및 토의
• 팀 프로젝트 (발표)

기초지식 및 도구능력

평가

- Research Report는 Cumulative 합니다.

교재 및 참고자료

• 바비 얼, (2021). 이성용,유홍준,정기선,고성호,이정환,민수홍,문용갑,정태인,김광기,김상욱,장준오 (역). 사회조사방법론. 센게이지러닝. 알라딘에서 책
  • 낮은 에디션도 무관
  • 원서도 무관
• 앤디 필드, 제레미 마일스, 조이 필드. (2020). 류광 (역). 앤디 필드의 유쾌한 R 통계학 (Discovering Statistics Using R). 알라딘
  • 낮은 에디션도 무관
  • 원서도 무관
  • Andy Field, Jeremy Miles, Zoe Field. (2012). Discovering Statistics using R. Sage Publication. OR

—-
참고도서

• Andy Field. (2013). Discovering Statistics using IBM SPSS Statistics. Sage Publication.
• 안재형 (2011). R을 이용한 누구나 하는 통계분석. 한나래.
• Futher Reading
  • Nina ZumelJohn Mount. (2014). Practical Data Science with R. Manning

Schedule

Schedule page

1. Week 1: Introdoction
2. Week 2: Preliminary RQ / Investigating previous research works / RQ develpment / Hypothesis development
3. Week 3: Use of library / RQ and Hypotheses Building | Design of Study | Data, what to do with them?
4. Week 4: Standard scores | Sampling, SE, CLT | Ch. 9. One vs Two samples Comparison
5. Week 5: Ch.10 ANOVA | Two way-ANOVA |
6. Week 6: r / Regression | Chi-square
7. Week 7: Present your research questions
8. Week 8: Midterm Period
9. Week 9: Regression: Chapter 7 (Multiple Regression + alpha) & 8 (Logistic Regression)
10. Week 10: Ch. 11. ANCOVA / Ch. 12. Factorial ANOVA
11. Week 11: Ch. 13. Repeated Design / Ch. 14. Mixed Design
12. Week 12: Ch. 16. Manova / Ch. 17. Exploratory Factor Analysis
13. Week 13: SNA . . .
14. Week 14: Presentation
15. Week 15: Presentation
16. Week 16: Final Period

Announcement