Hiroshima University Syllabus

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Japanese
Academic Year 2024Year School/Graduate School School of Integrated Arts and Sciences Department of Integrated Global Studies
Lecture Code ARC01401 Subject Classification Specialized Education
Subject Name Social Statistics Analysis I (社会統計・データ分析 I)
Subject Name
(Katakana)
シャカイトウケイ・データブンセキ I
Subject Name in
English
Social Statistics Analysis I
Instructor NUNES TENDEIRO JORGE
Instructor
(Katakana)
ナヌッシュ テンデイル ジョージ
Campus Higashi-Hiroshima Semester/Term 2nd-Year,  First Semester,  1Term
Days, Periods, and Classrooms (1T) Weds7-8:IAS K110
Lesson Style Lecture Lesson Style
(More Details)
 
Lectures we be conducted in-class only. 
Credits 1.0 Class Hours/Week   Language of Instruction E : English
Course Level 3 : Undergraduate High-Intermediate
Course Area(Area) 24 : Social Sciences
Course Area(Discipline) 05 : Sociology
Eligible Students
Keywords Social sciences, statistics, R, descriptives, inference 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students)
 
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students)
Integrated Global Studies
(Knowledge and Understanding)
・The knowledge and understanding of the important characteristics and basic theoretical framework of individual academic disciplines. 
Class Objectives
/Class Outline
I will give lectures on the way of thinking about data, from collection through reporting findings. Performing descriptive analyses and mastering the basics of statistical inference are at the core of this course. Also, the programming language R will be taught and used in order to apply statistics to data. 
Class Schedule lesson1: Gentle introduction to statistics
lesson2: Getting started with R
lesson3: Additional R concepts
lesson4: Descriptive statistics
lesson5: Drawing graphs. Basic programming
lesson6: Introduction to probability
lesson7: Estimation (Part 1/2)
lesson8: Estimation (Part 2/2)
lesson9: Hypothesis testing (Part 1/2)
lesson10: Hypothesis testing (Part 2/2)
lesson11: Categorical data analysis
lesson12: Comparing two means
lesson13: Comparing several means (one-way ANOVA)
lesson14: Linear regression (Part 1/2)
lesson15: Linear regression (Part 1/2)

Examination will consist of working on and submitting several assignments.

This course has to be taken together with Social Statistics Analysis II (ARC01501). 
Text/Reference
Books,etc.
Navarro, D. (2015). Learning statistics with R: A tutorial for psychology students and other beginners. (Version 0.6). University of New South Wales, Sydney, Australia. R package version
0.5.1, https://learningstatisticswithr.com. 
PC or AV used in
Class,etc.
 
(More Details) The course includes lecture slides (PDF) and assignment files (PDF, text files). On occasion, videos may be suggested. 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
It is best to work regularly. Follow the lectures sequence. Do use R either via RStudio Cloud or, (optionally) install it on your laptop. Reproduce all examples discussed in the lectures on your own. Work carefully through the assignments. 
Requirements This course has to be taken together with Social Statistics Analysis II (ARC01501). 
Grading Method The evaluation is based on assignments (100%). 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message  
Other This course has to be taken together with Social Statistics Analysis II (ARC01501). 
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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