SemesterFall Semester, 2020
DepartmentInternational Master's Program in Asia-Pacific Studies, First Year
Course NameIntroduction to Statistical Analysis
Instructor
Credit3.0
Course TypeElective
Prerequisite
Course Objective
Course Description
Course Schedule

 




































































































































































週次Week



課程主題Course Theme



課程內容與指定閱讀Content and Reading Assignment



教學活動與作業Activity and Homework



學習投入時數Estimated time devoted to coursework per week



課堂講授Lecture Hours



課程前後Preparation Time



1



Introduction



Introduction



TBA



3.0



4.5



2



Statistics and Social Research



Ch. 1



TBA



3.0



4.5



3



Mid-Autumn Festival



 



 



 



 



4



Descriptive Statistics I



Ch. 2



TBA



3.0



4.5



5



Descriptive Statistics II



Ch. 3



TBA



3.0



4.5



6



Probability Distribution I



Ch. 4



TBA



3.0



4.5



7



Probability Distribution II



Ch. 4



TBA



3.0



4.5



8



1st quiz and Review



Ch. 5



Quiz



3.0



4.5



9



Estimation



Ch. 6



TBA



3.0



4.5



10



Statistical Inference I



Ch. 6



TBA



3.0



4.5



11



Statistical Inference II



Ch. 7



TBA



3.0



4.5



12



2nd quiz and Review



Ch. 7



TBA



3.0



4.5



13



Comparison of Two Groups



Ch. 8



TBA



3.0



4.5



14



Analyzing Association between Categorical Variables I



Ch. 8



TBA



3.0



4.5



15



Analyzing Association between Categorical Variables II



Ch. 12



TBA



3.0



4.5



16



Comparing Groups: ANOVA I



Ch. 12



TBA



3.0



4.5



17



Linear Regression and Correlation



Ch. 10



TBA



3.0



4.5



18



Final Exam



Review



Final exam



3.0



4.5



Teaching Methods
Teaching Assistant

TBA


Requirement/Grading

Course Requirements 

Attendance: 

Class attendance is required. Unlike some other sociology courses, statistics requires you to gradually but constantly build your knowledge and skills. It is very difficult to catch up once you get behind. You are also expected to contribute to the class by asking questions, participating in class discussions, and working with each other for in-class exercises. Therefore, your attendance is essential for making these contributions. 



Reading Assignments: 

You are expected to read the assigned chapters before you come to each session. In order to successfully complete reading assignments, you need to understand what is in each chapter. In addition to highlighting the text and taking notes, I suggest you write down any specific questions. 

You may find some chapters difficult to follow. Don’t worry if this happens. It is important to finish reading the assigned chapter before each session to get a general idea about the chapter and go back to it after class to make sure that you understand the materials better. 



Problem Solving Assignments: 

Learning by doing is very important for your understanding of statistics. There will be exercise questions given to you at the end of most sessions. You will have at least a week to complete each assignment. If you start working on your assignments early, you will have a chance to ask questions in the next class session before submitting your assignments. 

I will collect assignments at the beginning of the scheduled class sessions. If you turn in your assignments late (anytime after the class session starts and before 4:00 pm on the next day), you will lose points. Where to submit late assignments: To be arranged by the TA. 



Honor Code: 

Please help each other, by all means, to exchange notes for missed class sessions, study for exams, etc. The assignments that you turn in should be your own work, however. Any form of violation will result in a "zero" for that particular assignment or an "F" for the course, at my discretion. 



Grading: 

Problem Solving Assignments: 50% 

Tests (3 tests including final): 45% 

Attendance: 5%


Textbook & Reference

Agresti, Alan, 2018. Statistical Methods for the Social Sciences (Fifth Edition). Harlow, UK: Pearson Education Limited.



Navarro, Danielle. Learning Statistics with R. https://learningstatisticswithr.com/


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