Hiroshima University Syllabus

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Japanese
Academic Year 2020Year School/Graduate School Graduate School of Humanities and Social Sciences (Master's Course) Division of Humanities and Social Sciences Psychology Program
Lecture Code WMC10050 Subject Classification Specialized Education
Subject Name 心理学特講B
Subject Name
(Katakana)
 
Subject Name in
English
Special Lecture on Psychology B
Instructor NAKASHIMA KENICHIRO,SHIMIZU HISAYO,SUGIMURA KAZUMI,SUGIMURA SHINICHIRO,CHUJO KAZUMITSU,NAKAO TAKASHI,MORINAGA YASUKO,HIRAKAWA MAKOTO,UMEMURA TOMOTAKA,KAMBARA TOSHIMUNE,MORITA AIKO,YUZAWA MASAMICHI,MIYATANI MAKOTO
Instructor
(Katakana)
ナカシマ ケンイチロウ,シミズ ヒサヨ,スギムラ カズミ,スギムラ シンイチロウ,チュウジョウ カズミツ,ナカオ タカシ,モリナガ ヤスコ,ヒラカワ マコト,ウメムラ トモタカ,カンバラ トシムネ,モリタ アイコ,ユザワ マサミチ,ミヤタニ マコト
Campus Higashi-Hiroshima Semester/Term 1st-Year,  Second Semester,  Second Semester
Days, Periods, and Classrooms (2nd) Inte:To be announced.
Lesson Style Lecture Lesson Style
【More Details】
Lecture and exercise lesson, student oral presentation and discussion 
Credits 2 Class Hours/Week   Language on Instruction J : Japanese
Course Level 5 : Graduate Basic
Course Area(Area) 24 : Social Sciences
Course Area(Discipline) 06 : Psychology
Eligible Students M1/M2 students of Education and Human Science
Keywords Bayesian statistics, statistic modeling, psychometrics 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
 
Criterion referenced
Evaluation
 
Class Objectives
/Class Outline
In order to carry out research in psychology and to become an expert in advanced practice, it is essential to learn basic and applied research methods. The goal of this class is to provide students with specialized knowledge and skills related to psychological research methods such as experiments, surveys, observations, and interviews, as well as the analysis of the results.
Specifically, these research and analysis methods will be explained and discussed to deepen the understanding of these methods. Students will also discuss and consider research and analysis methods appropriate for their own research.

In this year,  we introduce statistical modeling and Bayesian estimation.
The purpose of this class is to learn theory of Bayesian statistical modeling and how to estimate probability models with Stan. 
Class Schedule lesson1  Orientation
lesson2  The trends of Bayesian statistics
lesson3  Bayesian statistical modeling.
lesson4  Probability distribution and likelihood
lesson5  Model evaluation
lesson6  Models with normal distribution
lesson7  Probabilistic programming languages
lesson8  Stan
lesson9  Generalized linear model
lesson10  Random effect model
lesson11  Generalized linear mixed model
lesson12  Statistical modeling in psychology
lesson13  Psychometrics and statistical modeling
lesson14  How to create original model
lesson15 general comment 
Text/Reference
Books,etc.
To be introduced in the class as required. 
PC or AV used in
Class,etc.
Handouts,image (video/PC/other image material) 
Suggestions on
Preparation and
Review
To be introduced in the class through all lesson. 
Requirements  
Grading Method Students to be comprehensively assessed by the materials of presentations, and participation and contribution in discussions and participation in classes. 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message  
Other   
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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