＜概要/Course Content Summary＞
This course aims to serve as an introduction to statistics, data science, and programming for the social sciences. We explore fundamentals of data visualization techniques, statistical testing procedures, and programming and apply them to real-world data. A wide variety of practical examples and problems (drawn from academic and government sources, industrial, commercial, and business sectors, and current events) that are conducive to understanding the concepts and their practicality will be provided in class. This is a practice-oriented course; using computers, we will conduct various forms of data visualization and statistical analysis throughout the course and gain practical experience with visualizing and analyzing data, designing surveys or experiments, and making statistical inferences and decisions.
＜到達目標/Goals,Aims＞
Our learning objectives are to:
• Understand fundamental concepts in statistics, data science, and programming.
• Understand the nature of probabilistic and statistical knowledge and the frameworks of statistical investigation.
• Develop basic skills in mathematical reasoning.
• Evaluate some of the advances in our understanding of various issues in the social sciences.
• Gain practical experience with visualizing and analyzing data, designing surveys or experiments, and making statistical inferences and decisions.
• Develop programming skills that are conducive to conducting effective and efficient quantitative research.
＜授業計画/Schedule＞
（実施回/
Week）
|
（内容/
Contents）
|
（授業時間外の学習/
Assignments）
|
|
（実施回/ Week）
Week 1
|
（内容/ Contents）
Introduction (why statistics?)
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapters 1-2 of Nakama and install R and RStudio.
|
|
（実施回/ Week）
Week 2
|
（内容/ Contents）
R and RStudio basics
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 2 of Nakama and solve homework problems.
|
|
（実施回/ Week）
Week 3
|
（内容/ Contents）
Fundamentals of programming: Creating plots
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapters 2-3 of Nakama and solve homework problems.
|
|
（実施回/ Week）
Week 4
|
（内容/ Contents）
Fundamentals of programming: Creating functions
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 3 of Nakama and solve homework problems.
|
|
（実施回/ Week）
Week 5
|
（内容/ Contents）
Descriptive statistics, data visualization
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 4 of Nakama and solve homework problems.
|
|
（実施回/ Week）
Week 6
|
（内容/ Contents）
Data visualization
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 4 of Nakama and solve homework problems.
|
|
（実施回/ Week）
Week 7
|
（内容/ Contents）
The framework of statistical hypothesis testing
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 5 of Nakama and solve homework problems.
|
|
（実施回/ Week）
Week 8
|
（内容/ Contents）
The two-sample t-test
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 6 of Nakama and perform a two-sample t-test.
|
|
（実施回/ Week）
Week 9
|
（内容/ Contents）
Midterm evaluation
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 6 of Nakama.
|
|
（実施回/ Week）
Week 10
|
（内容/ Contents）
One- and two-tailed tests
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 6 of Nakama and perform t-tests.
|
|
（実施回/ Week）
Week 11
|
（内容/ Contents）
The paired t-test
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 6 of Nakama and perform a paired t-test.
|
|
（実施回/ Week）
Week 12
|
（内容/ Contents）
The one-way analysis of variance (ANOVA)
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 7 of Nakama and perform a one-way ANOVA.
|
|
（実施回/ Week）
Week 13
|
（内容/ Contents）
Correlation analysis
|
（授業時間外の学習/ Assignments）
Assignment: Read Chapter 9 of Nakama and perform a correlation analysis.
|
|
（実施回/ Week）
Week 14
|
（内容/ Contents）
Additional topics in statistics, data visualization, and programming
|
（授業時間外の学習/ Assignments）
Assignment: Study for the final evaluation.
|
|
（実施回/ Week）
Week 15
|
（内容/ Contents）
Final evaluation
|
（授業時間外の学習/ Assignments）
|
Course Requirements and Assignments
a) Attendance, readings, and participation
You are required to attend the lectures and have an attendance record of at least 80%. You are also required to read lecture notes and solve homework problems each week. You are expected to actively contribute to class discussions.
b) Midterm examination
You are required to take an exam in Week 9. This is not an open-book exam.
c) Final examination
At the end of the course, you are required to take an exam. This is not an open-book exam.
Note: The schedule, requirements, and assignments will be subject to changes or revisions.
＜成績評価基準/Evaluation Criteria＞
|
Contributions to class discussions, attendance
|
10%
|
|
|
Assignment
|
30%
|
|
|
Examination
|
60%
|
|
Additional Information: Plagiarism and Cheating
Doshisha University does not tolerate plagiarism, cheating, or helping others to cheat. These actions will result in an automatic “F” in the course. Plagiarism is defined as misrepresenting the work of others (whether published or not) as your own. It may be inadvertent or intentional. Any facts, statistics, quotations, or paraphrasing of any information that is not common knowledge must be cited. For more information on paper writing, including how to avoid plagiarism and how to use citations, you can find many helpful resources in the library.
＜成績評価結果/Results of assessment＞
成績評価の見方について/Notes for assessment
| 登録者数 |
成績評価（%) |
評点
平均値 |
備考
|
| A |
B |
C |
D |
F |
他 |
| 15 |
60.0 |
6.7 |
20.0 |
0.0 |
13.3 |
0.0 |
3.0 |
|
＜テキスト/Textbook＞
|
Nakama, T.
, Quantitative Research Methods for the Social Sciences
.
(2019)
.
|
| |
＜備考/Remarks＞
INSTRUCTOR: Takehiko Nakama
EMAIL: nakama@jhu.edu
OFFICE HOURS: by appointment
Note: This syllabus will be subject to changes or revisions.
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